Automatic chord recognition is a fundamental and important task in music information processing. FifthNet is a recently proposed chord recognition framework based on a deep neural network (DNN). Its aim is to reduce the computational and memory loads by taking advantage of knowledge on music signals. Since FifthNet achieved the state-of-the-art performance and requires less computational resource compared to the other DNN-based methods, it seems suitable for real-time applications. However, the original FifthNet cannot be directly used in real-time because it applies the spectral reassignment method in its feature extractor. The reassignment method requires some look-ahead frames that results in unavoidable latency. In this paper, we propose to replace the reassignment method of FifthNet with the synchrosqueezing transform to reduce the amount of required look-ahead frames and the computational requirement. Our modification makes FifthNet on-line and removes the obstacle towards real-time execution. In addition, the experimental result shows that the accuracy of chord recognition can be improved by the proposed modification.

This paper presents a two-stage online phase reconstruction framework using causal deep neural networks (DNNs). Phase reconstruction is a task of recovering phase of the short-time Fourier transform (STFT) coefficients only from the corresponding magnitude. However, phase is sensitive to waveform shifts and not easy to estimate from the magnitude even with a DNN. To overcome this problem, we propose to use DNNs for estimating differences of phase between adjacent time-frequency bins. We show that convolutional neural networks are suitable for phase difference estimation, according to the theoretical relation between partial derivatives of STFT phase and magnitude. The estimated phase differences are used for reconstructing phase by solving a weighted least squares problem in a frame-by-frame manner. In contrast to existing DNN-based phase reconstruction methods, the proposed framework is causal and does not require any iterative procedure. The experiments showed that the proposed method outperforms existing online methods and a DNN-based method for phase reconstruction.

In this Letter, we propose to use Fresnel lenses for holographic sound-field imaging. Although a Fresnel lens has never been used for sound-field imaging mainly due to its low imaging quality, it has several desired properties, including thinness, lightweight, low cost, and ease of making a large aperture. We constructed an optical holographic imaging system composed of two Fresnel lenses used for magnification and demagnification of the illuminating beam. A proof-of-concept experiment verified that the sound-field imaging with Fresnel lenses is possible by using the spatiotemporally harmonic nature of sound.

Sound Event Localization and Detection (SELD) is a task of simultaneously identifying sound events and their locations. The existing methods perform SELD in the off-line setting using deep neural networks (DNNs) including bi-directional recurrent neural network (BiRNN). Although their effectiveness has been shown in the literature, they cannot be directly applied to real-time applications which requires on-line execution of SELD, i.e., the input signals must be successively processed with small latency. In this paper, we propose on-line extension of the off-line SELD systems and discuss about the essential latency of an on-line SELD system. The relationship between the system latency and accuracy of SELD was investigated by experiments. From the experimental results, we confirmed that on-line extension of the SELD system maintains or improves the performance of localization, while event detection performance is degraded in low-latency.

We recorded whistle sound radiated from a human mouth with parallel phase-shifting interferometry (PPSI) and applied beamformers to the measurement result in order to enhance the whistle sound. Optical instruments allow non-invasive measuring of sound fields. It is also useful for recording fields that microphones cannot be placed. PPSI with a high-speed polarization camera is one of the optical measuring systems, and various sound fields have been visualized with the system. However, the measured sound has much noise, and thus, signal-to-noise ratio (SNR) is not so high. Confirming a measured sound aurally is helpful for understanding the sound. In particular, recording near the mouth is required in many situations. In this paper, therefore, we recorded whistle sound with a high-speed polarization camera and visualized with PPSI. In addition, in order to reduce stationary noise, we applied delay-and-sum (DS) and minimum variance distortionless response (MVDR) beamformers to the measured data. The effectiveness of these beamformers in noise reduction was confirmed from the experiment result. The sound of whistle is enhanced much better by DS beamformer than MVDR beamformer. We analyzed these results and also discussed about the future works.

In this paper, we propose applying a high-speed polarization interferometer to underwater sound fields for their non-invasive visualization and temperature measurement. Underwater sound is usually measured by hydrophones that may disturb the sound field. To circumvent such disturbance, for airborne sound, a high-speed polarization interferometer has been proposed as a new measurement method. It enables non-contact measurement of non-stationary sound fields in air. This research applies the high-speed interferometer to underwater sound and confirms its capability of visualization. As an application, we also propose a non-invasive temperature measurement method that calculates temperature from the sound speed of visualized sound. As a result, we confirmed that the proposed method can measure the water temperature with an accuracy of about ±0:5 to 1.5°C.

In the field of nonstationary signal analysis and processing, the short-time Fourier transform (STFT) is frequently used to convert signals into the time-frequency domain. The instantaneous frequency (IF) of the STFT is defined as the time derivative of the STFT phase and plays an important role in the reassignment method and the synchrosqueezing transform (SST). In this paper, we propose a framework to design a window function for computing the IF of STFT. Computing the IF requires the STFT with a window and STFT with its derivative, i.e., the IF computation depends on both the window function and its derivative. To design a window suitable for computing the IF, we formulate the window design problem as a sidelobe minimization problem of the corresponding derivative. Two windows are designed considering the sidelobe energy or the highest sidelobe level as cost functions for minimizing the sidelobes of their derivatives. The SST using the proposed window provides a sharper time-frequency representation compared to those produced using ordinary bandwidth-adjustable windows.

Phase reconstruction from amplitude spectrograms has attracted attention in recent acoustics because of its potential applications in speech synthesis and enhancement. The most well-known algorithm in acoustics is based on alternating projection and called Griffin-Lim algorithm (GLA). At the same time, GLA is known as the Gerchberg-Saxton algorithm in optics, and a lot of its variants have been proposed independently of those in acoustics. In this paper, we propose to apply phase reconstruction algorithms developed in the optics community to acoustic applications and evaluate them using acoustical metrics. Specifically, we propose to apply the averaged alternating reflections (AAR), relaxed AAR (RAAR), and hybrid input-output (HIO) algorithms to acoustic signals. Our experimental results suggested that RAAR has enough potential for acoustic applications because it clearly outperformed GLA.

In this paper, we propose an audio declipping method that takes advantages of both sparse optimization and deep learning. Since sparsity-based audio declipping methods have been developed upon constrained optimization, they are adjustable and well-studied in theory. However, they always uniformly promote sparsity and ignore the individual properties of a signal. Deep neural network (DNN)-based methods can learn the properties of target signals and use them for audio declipping. Still, they cannot perform well if the training data have mismatches and/or constraints in the time domain are not imposed. In the proposed method, we use a DNN in an optimization algorithm. It is inspired by an idea called plug-and-play (PnP) and enables us to promote sparsity based on the learned information of data, considering constraints in the time domain. Our experiments confirmed that the proposed method is stable and robust to mismatches between training and test data.

Sound event localization and detection (SELD) is a combined task of identifying the sound event and its direction. Deep neural networks (DNNs) are utilized to associate them with the sound signals observed by a microphone array. Although ambisonic microphones are popular in the literature of SELD, they might limits the range of applications due to their predetermined geometry. Some applications (including those for pedestrians that perform SELD while walking) require a wearable microphone array whose geometry can be designed to suit the task. In this paper, for development of such a wearable SELD, we propose a dataset named Wearable SELD dataset. It consists of data recorded by 24 microphones placed on a head and torso simulators (HATS) with some accessories mimicking wearable devices (glasses, earphones, and headphones). We also provide experimental results of SELD using the proposed dataset and SELDNet to investigate the effect of microphone configuration.

Harmonic and percussive sound separation (HPSS) is a widely applied pre-processing tool that extracts distinct (harmonic and percussive) components of a signal. In the previous methods, HPSS has been performed based on the structural properties of magnitude (or power) spectrograms. However, such approach does not take advantage of phase that contains useful information of the waveform. In this paper, we propose a novel HPSS method named MipDroP that relies only on phase and does not use information of magnitude spectrograms. The proposed MipDroP algorithm effectively examines phase through its mixed partial derivative and constructs a pair of masks for the separation. Our experiments showed that MipDroP can extract percussive components better than the other methods.

Phase recovery is a methodology of estimating a phase spectrogram that is reasonable for a given amplitude spectrogram. For enhancing the signals obtained from the processed amplitude spectrograms, it has been applied to several audio applications such as harmonic/percussive source separation (HPSS). Because HPSS is often utilized as preprocessing of other processes, its phase recovery should be simple. Therefore, practically effective methods without requiring much computational cost, such as phase unwrapping (PU), have been considered in HPSS. However, PU often results in a phase that is completely different from the true phase because (1) it does not consider the observed phase and (2) estimation error is accumulated with time. To circumvent this problem, we propose a phase-recovery method for HPSS using the observed phase information. Instead of accumulating the phase as in PU, we formulate a local optimization model based on the observed phase so that the estimated phase remains similar to the observed phase. The analytic solution to the proposed optimization model is provided to keep the computational cost cheap. In addition, iterative refinement of phase in the existing methods is applied for further improving the result. From the experiments, it was confirmed that the proposed method outperformed PU.

To simulate the sound field based on the real environment, it is essential to know the geometry of room and its acoustic impedances. Recently, the geometry of room can be measured easily using measurements such as Mixed Reality (MR) technology and a laser range finder. However, it is not easy to obtain the acoustic impedances on the surface of rooms by in-situ measurements. On the other hand, with the development of numerical simulation technology, the previous studies have proposed a method for estimating acoustic impedances using the recorded signals from the microphones and sound field simulation. However, for practical use, acoustic impedance estimation that is robust to the errors in the measurement positions is required. In our previous works, we also proposed the measurement system of sound intensities using MR technology. The system can quickly measure the multiple sound intensities and visualizes the measurement results as 3DCG in real time at the measurement position. In this study, we propose the estimation method of acoustic impedances of walls using the measurement of sound intensities at multiple points and FDTD simulation. From the simulations experiments with the positional errors in measurement points, the proposed method improved estimation accuracies by about 30 dB compared to the conventional method with time-signals. In addition, the accuracy was improved by about 8 dB by increasing the number of measurement points.

To a achieve highly immersive auditory experience, physically accurate sound field reproduction is required. Many local sound field synthesis (SFS) methods have been proposed to accurately reproduce the sound field around a listener. However, the narrow listening area in local SFS prevents the listener from moving freely. In this study, we developed a dynamic 2.5-dimensional local SFS system, which moves the listening area to follow the movements of the listener using a body-tracking camera. For the evaluation the proposed system, the azimuth localization accuracy was investigated by measuring interaural level differences in an anechoic chamber. The results show that when the distance between the listener and the virtual point source is 1.0 m, the proposed system has a small azimuthal localization error compared with conventional SFS.

Audio declipping aims to reconstruct the original signal from a clipped observed signal. Clipping has a negative effect on subsequent multichannel processing such as beamforming. This is because the channel-wise nonlinear distortion deteriorates the spatial covariance matrix in the time-frequency domain. Hence, it is important to consider multichannel audio declipping that explicitly takes into account the subsequent audio signal processing. However, most of the existing methods have been developed for the single-channel case. In this paper, we propose a joint optimization method for declipping and beamforming. The multichannel declipped signal and the spatial filter are jointly optimized to sparsify the output of beamforming. Our experimental results show the effectiveness of the proposed method compared to the beamforming with prior declipping.

In this paper, we propose a phase-aware audio inpainting method and its variations. The aim of audio inpainting is to restore some gaps of audio signals. Among various methods, sparsity-based methods have been studied, especially for restoring gaps up to 50 ms. However, they usually focus only on the magnitude information even though the phase information is also available. In the proposed method, we utilize a phase-aware prior to induce smoothness of phase. The variations of the basic algorithm are also obtained by applying some updating schemes. The numerical results show effectiveness of the proposed methods, especially for longer gaps.

Nonstationary signals are commonly analyzed and processed in the time-frequency (T-F) domain that is obtained by the discrete Gabor transform (DGT). The T-F representation obtained by DGT is spread due to windowing, which may degrade the performance of T-F domain analysis and processing. To obtain a well-localized T-F representation, sparsity-aware methods using '1-norm have been studied. However, they need to discretize a continuous parameter onto a grid, which causes a model mismatch. In this paper, we propose a method of estimating a sparse T-F representation using atomic norm. The atomic norm enables sparse optimization without discretization of continuous parameters. Numerical experiments show that the T-F representation obtained by the proposed method is sparser than the conventional methods.

© 2020 Elsevier Ltd Accurate determination of microphone sensitivity is important to build reliable acoustical instruments. The sensitivity is usually determined by calibration. However, because available microphone calibration methods determine the sensitivity from a mathematical model derived from the geometry of a conventional condenser microphone, they cannot be applied to the calibration of microelectromechanical systems (MEMS) microphone straightforwardly. To compromise this geometry difference with the available calibration methods, some authors have proposed the development of adapters that fits the conventional calibration apparatus and modified the calibration procedure. In this paper, we propose a different approach to calibrate the MEMS microphone. The sensitivity is calculated directly from the measurement of the sound field applied to the MEMS microphone and its output voltage. The projection of the sound field is measured by parallel phase-shifting interferometry (PPSI), and sound pressure on the MEMS microphone is obtained by tomographic reconstruction. Experimental calibration of a MEMS microphone was performed and validated using a microphone substitution method to evaluate the discrepancies of the sensitivity result. It is shown that the proposed method can be used to determine the frequency response of the MEMS microphone in the frequency range of 1000 Hz to 12000 Hz.

Optical interferometric measurement methods for sound fields have garnered considerable attention owing to their contactless nature. The capabilities of non-invasive measurement and reconstruction of three-dimensional sound fields are significant for characterizing acoustic transducers. However, three-dimensional reconstructions are typically time consuming because of the two-dimensional scanning and rotation of the measurement system. This paper presents a scan and rotation-free reconstruction of an axisymmetric sound field in the human hearing range. A physical-model-based algorithm is proposed to reconstruct an axisymmetric sound field from optical interferograms recorded using parallel phase-shifting interferometry and a high-speed polarization camera. We demonstrate that audible sound fields can be reconstructed from data measured in 10 ms. The proposed method is effective for the rapid evaluation of axially symmetric acoustic transducers.

Sound fields radiated from the castanet, a Spanish percussive instrument comprising two shells, were optically visualized. A measurement system, which used parallel phase-shifting interferometry and a high-speed polarization camera, enabled the capture of instantaneous sound fields around the castanets, while the castanets were played, with the spatial resolution of 1.1 mm and frame rate of 100 000 fps. By carefully aligning the tilt of the castanets, the sound fields within the 1-mm gaps between both the shells were captured. From the visualization results, two acoustic resonances between the shells were identified. The first mode appeared between 1000 and 2000 Hz and exhibited a frequency chirp of several hundred hertz for several milliseconds after the impact. This can be explained by the Helmholtz resonance with a time-varying resonator shape, which is caused by the movement of the shells after impact. The second mode showed a resonance pattern with a single nodal diameter at the center of the shells, i.e., the standing wave mode caused by the interior volume. These physical phenomena involved in the sound radiation were identified owing to the unique features of the optical imaging method, such as contactless nature and millimeter-resolution imaging of instantaneous pressure fields.

Detecting sound source objects within visual observation is important for autonomous robots to comprehend surrounding environments. Since sounding objects have a large variety with different appearances in our living environments, labeling all sounding objects is impossible in practice. This calls for self-supervised learning which does not require manual labeling. Most of conventional self-supervised learning uses monaural audio signals and images and cannot distinguish sound source objects having similar appearances due to poor spatial information in audio signals. To solve this problem, this paper presents a self-supervised training method using 360 images and multichannel audio signals. By incorporating with the spatial information in multichannel audio signals, our method trains deep neural networks (DNNs) to distinguish multiple sound source objects. Our system for localizing sound source objects in the image is composed of audio and visual DNNs. The visual DNN is trained to localize sound source candidates within an input image. The audio DNN verifies whether each candidate actually produces sound or not. These DNNs are jointly trained in a self-supervised manner based on a probabilistic spatial audio model. Experimental results with simulated data showed that the DNNs trained by our method localized multiple speakers. We also demonstrate that the visual DNN detected objects including talking visitors and specific exhibits from real data recorded in a science museum.

Monaural source separation is often conducted by manipulating the amplitude spectrogram of a mixture (e.g., via time-frequency masking and spectral subtraction). The obtained amplitudes are converted back to the time domain by using the phase of the mixture or by applying phase reconstruction. Although phase reconstruction performs well for the true amplitudes, its performance is degraded when the amplitudes contain error. To deal with this problem, we propose an optimization-based method to refine both amplitudes and phases based on the given amplitudes. It aims to find time-domain signals whose amplitude spectrograms are close to the given ones in terms of the generalized alpha-beta divergences. To solve the optimization problem, the alternating direction method of multipliers (ADMM) is utilized. We confirmed the effectiveness of the proposed method through speech-nonspeech separation in various conditions.

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Aerodynamic sound is one of the causes of noise in high-speed trains, automobiles, and wind turbines. To investigate the characteristics of aerodynamic sound generation, measurements around the sound sources are required. Aerodynamic sound is typically measured using microphones. However, microphones cannot capture the near-field of aerodynamic sound because they become new noise sources inside the air flow. To observe the aerodynamic sound near-field, we performed two-dimensional visualization of aerodynamic sound using an optical method. The optical method used in this research, parallel phase-shifting interferometry (PPSI), can detect the pressure within the measurement area as variations of the phase of light. PPSI can therefore visualize the pressure fields. We visualized both the sound pressure and flow components of the sound generated by flow around a square cylinder and flat plates. The visualized pressure fields are provided as animations in the online resources. Analysis of the sound and flow component time variations confirmed the correlations between them.


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In recent single-channel speech enhancement, deep neural network (DNN) has played a quite important role for achieving high performance. One standard use of DNN is to construct a maskgenerating function for time-frequency (T-F) masking. For applying a mask in T-F domain, the shorttime Fourier transform (STFT) is usually utilized because of its well-understood and invertible nature. While the mask-generating regression function has been studied for a long time, there is less research on T-F transform from the viewpoint of speech enhancement. Since the performance of speech enhancement depends on both the T-F mask estimator and T-F transform, investigating T-F transform should be beneficial for designing a better enhancement system. In this paper, as a step toward optimal T-F transform in terms of speech enhancement, we experimentally investigated the effect of parameter settings of STFT on a DNN-based mask estimator. We conducted the experiments using three types of DNN architectures with three types of loss functions, and the results suggested that U-Net is robust to the parameter setting while that is not the case for fully connected and BLSTM networks.

Visualizing sound field is important to fully understand the acoustic behavior and phenomena. Recently, sound field visualization by using parallel phase-shifting interferometer (PPSI) has been proposed. PPSI can observe sound field quantitively and instantaneously without placing any object inside the field. However, the system has introduced some unwanted noise to the output fringe image. There is continuous development in signal processing method to reduce the noise in PPSI system. In this paper, different type of spatio-temporal filter has been tested to improve noise reduction in PPSI system upon establishing.

© 2020 IEEE. We propose an end-to-end speech enhancement method with trainable time-frequency (T-F) transform based on invertible deep neural network (DNN). The resent development of speech enhancement is brought by using DNN. The ordinary DNN-based speech enhancement employs T-F transform, typically the short-time Fourier transform (STFT), and estimates a T-F mask using DNN. On the other hand, some methods have considered end-to-end networks which directly estimate the enhanced signals without T-F transform. While end-to-end methods have shown promising results, they are black boxes and hard to understand. Therefore, some end-to-end methods used a DNN to learn the linear T-F transform which is much easier to understand. However, the learned transform may not have a property important for ordinary signal processing. In this paper, as the important property of the T-F transform, perfect reconstruction is considered. An invertible nonlinear T-F transform is constructed by DNNs and learned from data so that the obtained transform is perfectly reconstructing filterbank.

© 2020 IEEE. The short-time Fourier transform (STFT) is widely employed in non-stationary signal analysis, whose property depends on window functions. Instantaneous frequency in STFT, the time-derivative of phase, is recently applied to many applications including spectrogram reassignment. The computation of instantaneous frequency requires STFT with the window and STFT with the (time-)differential window, i.e., the computation of instantaneous frequency depends on both the window function and its time derivative. To obtain the instantaneous frequency accurately, the sidelobe of frequency response of differential window should be reduced because the side-lobe causes mixing of multiple components. In this paper, we propose window functions suitable for computing the instantaneous frequency which are designed based on minimizing the sidelobe energy of the frequency response of the differential window.

© 2020 IEEE We propose a speech enhancement method using a causal deep neural network (DNN) for real-time applications. DNN has been widely used for estimating a time-frequency (T-F) mask which enhances a speech signal. One popular DNN structure for that is a recurrent neural network (RNN) owing to its capability of effectively modelling time-sequential data like speech. In particular, the long short-term memory (LSTM) is often used to alleviate the vanishing/exploding gradient problem which makes the training of an RNN difficult. However, the number of parameters of LSTM is increased as the price of mitigating the difficulty of training, which requires more computational resources. For real-time speech enhancement, it is preferable to use a smaller network without losing the performance. In this paper, we propose to use the equilibriated recurrent neural network (ERNN) for avoiding the vanishing/exploding gradient problem without increasing the number of parameters. The proposed structure is causal, which requires only the information from the past, in order to apply it in real-time. Compared to the uni- and bi-directional LSTM networks, the proposed method achieved the similar performance with much fewer parameters.

© 2020 IEEE. Phase reconstruction, which estimates phase from a given amplitude spectrogram, is an active research field in acoustical signal processing with many applications including audio synthesis. To take advantage of rich knowledge from data, several studies presented deep neural network (DNN)-based phase reconstruction methods. However, the training of a DNN for phase reconstruction is not an easy task because phase is sensitive to the shift of a waveform. To overcome this problem, we propose a DNN-based two-stage phase reconstruction method. In the proposed method, DNNs estimate phase derivatives instead of phase itself, which allows us to avoid the sensitivity problem. Then, phase is recursively estimated based on the estimated derivatives, which is named recurrent phase unwrapping (RPU). The experimental results confirm that the proposed method outperformed the direct phase estimation by a DNN.

In this paper, we propose a phase reconstruction framework, named Deep Griffin-Lim Iteration (DeGLI). Phase reconstruction is a fundamental technique for improving the quality of sound obtained through some process in the time-frequency domain. It has been shown that the recent methods using deep neural networks (DNN) outperformed the conventional iterative phase reconstruction methods such as the Griffin-Lim algorithm (GLA). However, the computational cost of DNN-based methods is not adjustable at the time of inference, which may limit the range of applications. To address this problem, we combine the iterative structure of GLA with a DNN so that the computational cost becomes adjustable by changing the number of iterations of the proposed DNN-based component. A training method that is independent of the number of iterations for inference is also proposed to minimize the computational cost of the training. This training method, named sub-block training by denoising (SBTD), avoids recursive use of the DNN and enables training of DeGLI with a single sub-block (corresponding to one GLA iteration). Furthermore, we propose a complex DNN based on complex convolution layers with gated mechanisms and investigated its performance in terms of the proposed framework. Through several experiments, we found that DeGLI significantly improved both objective and subjective measures from GLA by incorporating the DNN, and its sound quality was comparable to those of neural vocoders.

© 2019 IEEE. Decomposition of an audio mixture into harmonic and percussive components, namely harmonic/percussive source separation (HPSS), is a useful pre-processing tool for many audio applications. Popular approaches to HPSS exploit the distinctive source-specific structures of power spectrograms. However, such approaches consider only power spectrograms, and the phase remains intact for resynthesizing the separated signals. In this paper, we propose a phase-aware HPSS method based on the structure of the phase of harmonic components. It is formulated as a convex optimization problem in the time domain, which enables the simultaneous treatment of both amplitude and phase. The numerical experiment validates the effectiveness of the proposed method.

© 2019 IEEE. Recent development of optical interferometry enables us to measure sound without placing any device inside the sound field. In particular, parallel phase-shifting interferometry (PPSI) has realized advanced measurement of refractive index of air. Its novel application investigated very recently is simultaneous visualization of flow and sound, which had been difficult until PPSI enabled high-speed and accurate measurement several years ago. However, for understanding aerodynamic sound, separation of air flow and sound is necessary since they are mixed up in the observed video. In this paper, guided-spatio-temporal filtering is proposed to separate sound from the optically measured images. Guided filtering is combined with a physical-model-based spatio-temporal filterbank for extracting sound-related information without the undesired effect caused by the image boundary or occluding objects. Such image boundary and occluding objects are typical difficulty arose in signal processing of an optically measured sound filed.

© 2019 IEEE. Low-rankness of amplitude spectrograms has been effectively utilized in audio signal processing methods including non-negative matrix factorization. However, such methods have a fundamental limitation owing to their amplitude-only treatment where the phase of the observed signal is utilized for resynthesizing the estimated signal. In order to address this limitation, we directly treat a complex-valued spectrogram and show a complex-valued spectrogram of a sum of sinusoids can be approximately low-rank by modifying its phase. For evaluating the applicability of the proposed low-rank representation, we further propose a convex prior emphasizing harmonic signals, and it is applied to audio denoising.

© 2019 IEEE. We propose a data-driven design method of perfect-reconstruction filterbank (PRFB) for sound-source enhancement (SSE) based on deep neural network (DNN). DNNs have been used to estimate a time-frequency (T-F) mask in the short-time Fourier transform (STFT) domain. Their training is more stable when a simple cost function as mean-squared error (MSE) is utilized comparing to some advanced cost such as objective sound quality assessments. However, such a simple cost function inherits strong assumptions on the statistics of the target and/or noise which is often not satisfied, and the mismatch of assumption results in degraded performance. In this paper, we propose to design the frequency scale of PRFB from training data so that the assumption on MSE is satisfied. For designing the frequency scale, the warped filterbank frame (WFBF) is considered as PRFB. The frequency characteristic of learned WFBF was in between STFT and the wavelet transform, and its effectiveness was confirmed by comparison with a standard STFT-based DNN whose input feature is compressed into the mel scale.

© 2019 IEEE. This paper presents a novel phase reconstruction method (only from a given amplitude spectrogram) by combining a signal-processing-based approach and a deep neural network (DNN). To retrieve a time-domain signal from its amplitude spectrogram, the corresponding phase is required. One of the popular phase reconstruction methods is the Griffin-Lim algorithm (GLA), which is based on the redundancy of the short-time Fourier transform. However, GLA often involves many iterations and produces low-quality signals owing to the lack of prior knowledge of the target signal. In order to address these issues, in this study, we propose an architecture which stacks a sub-block including two GLA-inspired fixed layers and a DNN. The number of stacked sub-blocks is adjustable, and we can trade the performance and computational load based on requirements of applications. The effectiveness of the proposed method is investigated by reconstructing phases from amplitude spectrograms of speeches.

© 2019 Author(s). In order to incorporate a directive sound source into acoustic simulation using the finite-difference time-domain method (FDTD), this paper proposes an optimization-based method to estimate the initial value which approximates a desired directional pattern after propagation. The proposed method explicitly considers a discretized FDTD scheme and optimizes the initial value directly in the time domain so that every effect of the discretization error of FDTD, including numerical dispersion, is taken into account. It is also able to consider a frequency-wise directivity by integrating the Fourier transform into the optimization procedure, even though the estimated result is defined in the time domain. After the optimization, the obtained result can be utilized in any acoustic simulation based on the same FDTD scheme without modification because the result is represented as the initial value to be propagated and no additional procedure is required.

© 1994-2012 IEEE. Recovering a signal from its amplitude spectrogram, or phase recovery, exhibits many applications in acoustic signal processing. When only an amplitude spectrogram is available and no explicit information is given for the phases, the Griffin-Lim algorithm (GLA) is one of the most utilized methods for phase recovery. However, GLA often requires many iterations and results in low perceptual quality in some cases. In this letter, we propose two novel algorithms based on GLA and the alternating direction method of multipliers (ADMM) for better recovery with fewer iteration. Some interpretation of the existing methods and their relation to the proposed method are also provided. Evaluations are performed with both objective measure and subjective test.

© 2019 SPIE. We have proposed a method of simultaneously measuring aerodynamic sound and fluid ow using parallel phase- shifting interferometry (PPSI). PPSI can observe phase of light instantaneously and quantitatively. This method is useful for understanding the aerodynamic sound because PPSI can measure near the source of the aerodynamic sound. However, the components of sound and ow should be separated in order to observe detail near the source of sound inside a region of ow. Therefore, we consider a separation of the component of sound from simultaneously visualized images of sound and ow. In previous research, a spatio-temporal filter was used to extract a component satisfying the wave equation. The ow and the sound are different physical phenomena, and the ow cannot be expressed by the wave equation. Hence, we think that the spatio-temporal filter enables us to separate the component of sound from the simultaneously visualized images. In this paper, we propose a method for separation of ow and sound using spatio-temporal filter in order to visualize the component of the aerodynamic sound near its source. We conducted an experiment of the separation of data measured by PPSI. The results show that the spatio-temporal filter can extract the sound from air-ow except for the sound near objects and boundaries.

©2019 The Acoustical Society of Japan. As importance of the phase of complex spectrogram has been recognized widely, many techniques have been proposed for handling it. However, several definitions and terminologies for the same concept can be found in the literature, which has confused beginners. In this paper, two major definitions of the short-time Fourier transform and their phase conventions are summarized to alleviate such complication. A phase-aware signal-processing scheme based on phase conversion is also introduced with a set of executable MATLAB functions (https://doi.org/10/c3qb).

© 2019 Acoustical Society of Japan. All rights reserved. For musical instrument sounds containing partials, which are referred to as modes, the decaying processes of the modes significantly affect the timbre of musical instruments and characterize the sounds. However, their accurate decomposition around the onset is not an easy task, especially when the sounds have sharp onsets and contain the non-modal percussive components such as the attack. This is because the sharp onsets of modes comprise peaky but broad spectra, which makes it difficult to get rid of the attack component. In this paper, an optimization-based method of modal decomposition is proposed to overcome it. The proposed method is formulated as a constrained optimization problem to enforce the perfect reconstruction property which is important for accurate decomposition and causality of modes. Three numerical simulations and application to the real piano sounds confirm the performance of the proposed method.

© INTER-NOISE 2019 MADRID - 48th International Congress and Exhibition on Noise Control Engineering. All Rights Reserved. Optical measurement of sound play an important role to understand the physical natures and spatial distributions of sound. The optical measurement of sound is especially useful under the conditions where microphones cannot be installed such as inside high-temperature fields, narrow spaces, and flow fields. Flow-induced sound generated by parallel plates is one of such situations. The measurement of the sound by microphones is difficult because the spaces between plates are narrow and the objective sound is inside flow fields. While previous research investigates the pressure field including sound fields between flat plates by computer simulations, experimental measurement have not been well investigated. In this paper, we performed the measurement of the aerodynamic sound generated by flat plates inside a flow field by parallel phase-shifting interferometry in order to experimentally capture the sound field including spaces between flat plates. The result shows that the phases of sound between plates were opposite, which is consistent with the simulation in prior research.

© 2018 Elsevier Ltd In this paper, a sound source localization method for simultaneously estimating both direction-of-arrival (DOA) and distance from the microphone array is proposed. For estimating distance, the off-grid problem must be overcome because the range of distance to be considered is quite broad and even not bounded. The proposed method estimates the positions based on a modified version of the convex clustering method combined with the sparse coefficients estimation. A method for constructing a suitable monopole dictionary based on the coherence is also proposed so that the convex clustering based method can appropriately estimate distance of the sound sources. Numerical and measurement experiments were performed to investigate the performance of the proposed method.

© 2018 IEEE. The piano is one of the most popular and attractive musical instruments that leads to a lot of research on it. To synthesize the piano sound in a computer, many modeling methods have been proposed from full physical models to approximated models. The focus of this paper is on the latter, approximating piano sound by an IIR filter. For stably estimating parameters, the Kautz model is chosen as the filter structure. Then, the selection of poles and excitation signal rises as the questions which are typical to the Kautz model that must be solved. In this paper, sparsity based construction of the Kautz model is proposed for approximating piano sound.

© 2018 IEEE. In optimization-based signal processing, the so-called prior term models the desired signal, and therefore its design is the key factor to achieve a good performance. For audio signals, the time-directional total variation applied to a spectrogram in combination with phase correction has been proposed recently to model sinusoidal components of the signal. Although it is a promising prior, its applicability might be restricted to some extent because of the mismatch of the assumption to the signal. In this paper, based upon the previously proposed one, an improved prior for audio signals named instantaneous phase corrected total variation (iPCTV) is proposed. It can handle wider range of audio signals owing to the instantaneous phase correction term calculated from the observed signal.

© 2018 IEEE. Estimating envelope of a signal has various applications including empirical mode decomposition (EMD) in which the cubic C^2 -spline based envelope estimation is generally used. While such functional approach can easily control smoothness of an estimated envelope, the so-called undershoot problem often occurs that violates the basic requirement of envelope. In this paper, a tangentially constrained spline with tangential points optimization is proposed for avoiding the undershoot problem while maintaining smoothness. It is defined as a quartic C^2 -spline function constrained with first derivatives at tangential points that effectively avoids undershoot. The tangential points optimization method is proposed in combination with this spline to attain optimal smoothness of the estimated envelope.

© 2018 IEEE. For a musical instrument sound containing partials, or modes, the behavior of modes around the attack time is particularly important. However, accurately decomposing it around the attack time is not an easy task, especially when the onset is sharp. This is because spectra of the modes are peaky while the sharp onsets need a broad one. In this paper, an optimization-based method of modal decomposition is proposed to achieve accurate decomposition around the attack time. The proposed method is formulated as a constrained optimization problem to enforce the perfect reconstruction property which is important for accurate decomposition. For optimization, the alternating direction method of multipliers (ADMM) is utilized, where the update of variables is calculated in closed form. The proposed method realizes accurate modal decomposition in the simulation and real piano sounds.

© 2018 IEEE. Wave-based acoustic simulation methods are studied actively for predicting acoustical phenomena. Finite-difference time-domain (FDTD) method is one of the most popular methods owing to its straightforwardness of calculating an impulse response. In an FDTD simulation, an omnidirectional sound source is usually adopted, which is not realistic because the real sound sources often have specific directivities. However, there is very little research on imposing a directional sound source into FDTD methods. In this paper, a method of realizing a directional sound source in FDTD methods is proposed. It is formulated as an estimation problem of the initial value so that the estimated result corresponds to the desired directivity. The effectiveness of the proposed method is illustrated through some numerical experiments.

© 2018 Optical Society of America. In this Letter, a visualization method of a fluid flow through temperature control is proposed. The proposed method enables us to visualize an invisible fluid flow by controlling the temperature so that its visibility can be easily adjusted. Such ability of adjusting appearance is effective for visualizing the phenomena consisting of multiple physical processes. In order to verify the validity of the proposed method, the measurement experiment of visualization of both flow and sound in air using parallel phase-shifting interferometry, which is a similar condition to the previous research [Opt. Lett. 43, 991 (2018)], was conducted.

© 2018 Optical Society of America. Recent development of parallel phase-shifting interferometry (PPSI) enables accurate measurement of time-varying phase maps. By combining a high-speed camera with PPSI, it became possible to observe not only time-varying but also fast phenomena including fluid flow and sound in air. In such observation, one has to remove static phase (time-invariant or slowly-varying phase unrelated to the phenomena of interest) from the observed phase maps. Ordinarily, a signal processing method for eliminating the static phase is utilized after phase unwrapping to avoid the 2π discontinuity which can be a source of error. In this paper, it is shown that such phase unwrapping is not necessary for the high-speed observation, and a time-directional filtering method is proposed for removing the static phase directly from the wrapped phase without performing phase unwrapping. In addition, experimental results of simultaneously visualizing flow and sound with 42 000 fps are shown to illustrate how the time-directional filtering changes the appearance. A MATLAB code is included within the paper (also in https://goo.gl/N4wzdp) for aiding the understanding of the proposed method.

© 2018 Optical Society of America. In this Letter, simultaneous imaging of flow and sound by using parallel phase-shifting interferometry and a high-speed polarization camera is proposed. The proposed method enables the visualization of flow and sound simultaneously by using the following two factors: (i) injection of the gas, whose density is different from the surrounding air, makes the flow visible to interferometry, and (ii) time-directional processing is applied for extracting the small-amplitude sound wave from the high-speed flow video. An experiment with a frame rate of 42,000 frames per second for visualizing the flow and sound emitted from a whistle was conducted. By applying time-directional processing to the obtained video, both flow emitted from the slit of the whistle and a spherical sound wave of 8.7 kHz were successively captured.

Parametric speakers generate narrow directive sound field using modulated ultrasonic. Small size parametric speakers have a problem in sound quality. Demodulated audible sounds by parametric speakers have poor sound pressure in low and middle frequency bands due to the theory of the finite amplitude sound. The sound pressure of a demodulated sound monotonically increases as the frequency of the demodulated sound increases. To solve these problems, an ultrasonic transducer having a wide single peak or more than two peaks must be fabricated. Our previous paper proposed to use two resonant peaks which are close each other. Two close resonant peaks were obtained by two same sized diaphragms linked each other by a specially designed rod. In this paper, a transducer was developed to better structure which has durability against strong mechanical forces and two electrical inputs to control resonant modes of vibration. Durability was improved by optimization of the junction structure. The resonant mode control was enabled by a phase difference between two electrical signals applied to piezoelectric elements on two diaphragms. We succeeded in boosting mid-range sounds, by the newly developed transducer.

For speech communication, it is useful to emphasise the sound coming from a target direction. A large-scale microphone array enables a flexible design of the directivity pattern. However, it is difficult to implement a large-sale microphone array onto an ear-type hearing aid system. In this paper, we propose a hat-type hearing aid system composed of 48 MEMS microphones that can increase the flexibility of the sound directivity pattern. We found that it is possible to reduce the number of microphones to be used by considering the hat effect, without affecting the system performance. By compensating the time delays and reducing the number of microphones based on impulse response measurements, the directivity range of the sound directivity pattern was improved by 5 dB. In addition, we conducted a qualitative evaluation that resulted in an intelligibility improvement when using our hearing aid system.

Nowadays, many acoustical applications utilize microphone arrays whose configurations have a lot of varieties including linear, planar, spherical and random arrays. Arguably, some configurations are better than the others in terms of acquiring the spatial information of a sound field (for example, a spherical array can distinguish any direction of arrival, while a linear array cannot distinguish the direction perpendicular to its aperture direction due to the rotational symmetry). However, it is not easy to compare arrays of different configurations because each array has been treated by a specific theory depending on the configuration of the array. Although several criteria have been proposed for evaluating and/or designing the arrays, most of them are application-oriented criteria, and the best configuration for some criterion may not be a better one for the other criterion. Therefore, an analysis method for microphone arrays which does not depend on the array configuration or application is necessary. In this paper, the infinite-dimensional SVD is proposed for analyzing and comparing the properties of arrays. The singular values, functions and vectors obtained by the proposed method provide the fundamental properties of an array. (C) 2017 The Authors. Published by Elsevier Ltd.

© 2018 SPIE. Optical methods have been applied to visualize sound waves, and these have received a considerable amount of attention in both optical and acoustical communities. We have researched optical methods for sound imaging including laser Doppler vibrometry and Schlieren method. More recently, parallel phase-shifting interferometry with a high-speed polarization camera has been used, and it can take a slow-motion video of sound waves in the audible range. This presentation briefly reviews the recent progress in optical imaging of sound in air and introduces the applications including acoustic transducer testing and investigation of acoustic phenomena.

© 2018 The Acoustical Society of Japan. In marine seismic surveys to explore seafloor resources, the structure below the seafloor is estimated from the obtained sound waves, which are emitted by a marine seismic sound source and reflected or refracted between the layers below the seafloor. In order to estimate the structure below the seafloor from returned waves, information of the sound source position and the sound speed are needed. Marine seismic vibrators, which are one of the marine seismic sound sources, have some advantages such as high controllability of the frequency and phase of the sound, and oscillation at a high depth. However, when the sound source position is far from the sea surface, it becomes difficult to specify the exact position. In this paper, we propose a method to estimate the position of a marine seismic vibrator and the sound speed from obtained seismic data by formulating an optimization problem via hyperbolic Radon transform. Numerical simulations confirmed that the proposed method almost achieves theoretical lower bounds for the variances of the estimations.

© INTER-NOISE 2018 - 47th International Congress and Exposition on Noise Control Engineering: Impact of Noise Control Engineering. All rights reserved. In order to reduce aerodynamic noise, understanding the nature of aerodynamic sound sources is important. Generally, aerodynamic sound is measured by using microphones. However, microphones should be installed far from aerodynamic sound sources, which makes difficult to understand the nature of aerodynamic sound sources. As non-contact measurement methods, optical measurement methods of sound have been proposed. Among those, parallel phase-shifting interferometry (PPSI) can capture time-varying phenomena. Recently, simultaneous visualization of flow and sound using PPSI has been proposed. This method enables to capture the propagation of sound inside a flow. In this paper, as an application of aerodynamic sound visualization using PPSI, results of visualization of sound sources of edge tones are shown. The nozzle-edge distance and the flow rate, which are parameters of changing frequency of an edge tone, were adjusted from 5 mm to 13 mm at intervals of 1 mm and from 15 L/min to 45 L/min at intervals of 5 L/min, respectively. The frame rate of the high-speed camera in PPSI was set to 20,000 frames per second and the size of the visualization area was 77 mm by 56 mm. From the visualized images, the characteristics of spatial spread of edge tones were observed.

© INTER-NOISE 2018 - 47th International Congress and Exposition on Noise Control Engineering: Impact of Noise Control Engineering. All rights reserved. Measurement of sound pressure inside a tube is important for duct acoustics and microphone calibration. Inserting microphone directly into sound field will disturb the field and produce inaccurate measurement result. Recently, non-intrusive sound pressure measurement using optical techniques have been proposed. A laser Doppler vibrometer is used to measure line integrals of sound pressure yield projections and a reconstruction technique is then applied to recover the original sound field from projections. In this paper, measurement of sound pressure distribution using optical method is proposed to realize direct pressure measurement for microphone calibration. A simulation of sound field reconstruction from projections using filtered back-projection technique was developed and the performance was evaluated. The reconstruction performance was evaluated for the projection of plane wave and point source wave of frequency from 1000 Hz to 16000 Hz. The implementation of the proposed method for reconstruction of sound field inside an acrylic tube diameter 61.75 mm, length 22 mm, and thickness 3.5 mm for 1000 Hz sound source from projection using laser Doppler vibrometer was performed. The result shows that the proposed method was able to reconstruct the sound field inside tube and measure pressure distribution.

© INTER-NOISE 2018 - 47th International Congress and Exposition on Noise Control Engineering: Impact of Noise Control Engineering. All rights reserved. Visualization of a sound field is a powerful tool for understanding acoustic phenomena. Methods using a microphone array such as beamforming and near-field acoustic holography have widely been studied, and these have been applied to industrial problems. As alternative choices for the visualization of the sound field, optical methods have gained a considerable amount of attention due to their capability of non-intrusive measurement. These include laser Doppler vibrometry, Shadowgraphy, Schlieren method, optical digital holography, and parallel phase-shifting interferometry (PPSI). These methods are well developed for the visualization of propagating sound wave in a free field. Also, as these methods can observe the sound field without installing any instruments into the field to be measured, they have the potential to achieve visualization of sound inside a cavity, which is quite important for duct acoustics. This paper presents the single-shot visualization of the sound field inside a transparent cavity using PPSI with a high-speed camera, as well as the brief review of the development of the optical measurement of sound. For the experiments, the sound field inside of a ported speaker box made by acrylic plates was measured. Acoustics resonances and mode patterns inside the box were successively captured.

This paper presents a method of significantly improving the previously proposed simple, flexible, and accurate phase retrieval algorithm for the random phase-shifting interferometry named HEFS [K. Yatabe, J. Opt. Soc. Am. A 34, 87 (2017)]. Although its effectiveness and performance were confirmed by numerical experiments in the original paper, it is found that the algorithm may not work properly if observed fringe images contains untrusted (extremely noisy) pixels. In this paper, a method of avoiding such untrusted pixels within the estimation processes of HEFS is proposed for the practical use of the algorithm. In addition to the proposal, an experiment of measuring a sound field in air was conducted to show the performance for real data, where the proposed improvement is critical for that situation. MATLAB codes (which can be downloaded from http://goo.gl/upcsFe) are provided within the paper to aid understanding the main concept of the proposed methods. (C) 2017 Optical Society of America

© 2017 Copyright held by the owner/author(s). We propose a visualization system of three-dimensional (3D) sound information using video and optical see-through head mounted displays (ST-HMDs). The Mixed Reality (MR) displays enable intuitive understanding of 3D information of a sound field which is quite difficult to project onto an ordinary two-dimensional (2D) display in an easily understandable way. As examples of the visualization, the sound intensity (a stationary vector field representing the energy flow of sound) around a speaker and a motor engine is shown.

As an alternative to microphones, optical techniques have been studied for measuring a sound field. They enable contactless and non-invasive acoustical observation by detecting density variation of medium caused by sound. Although they have important advantages comparing to microphones, they also have some disadvantages. Since sound affects light at every points on the optical path, the optical methods observe an acoustical quantity as spatial integration. Therefore, point -wise information of a sound field cannot be obtained directly. Ordinarily, the computed tomography (CT) method has been applied for reconstructing a sound field from optically measured data. However, the observation process of the optical methods have not been considered explicitly, which limits the accuracy of the reconstruction. In this paper, a physical -model -based sound field reconstruction method is proposed. It explicitly formulates the physical observation process so that a model mismatch of the conventional methods is eliminated. (C) 2017 Elsevier Ltd. All rights reserved.

This paper presents a non-iterative phase retrieval method from randomly phase-shifted fringe images. By combining the hyperaccurate least squares ellipse fitting method with the subspace method (usually called the principal component analysis), a fast and accurate phase retrieval algorithm is realized. The proposed method is simple, flexible, and accurate. It can be easily coded without iteration, initial guess, or tuning parameter. Its flexibility comes from the fact that totally random phase-shifting steps and any number of fringe images greater than two are acceptable without any specific treatment. Finally, it is accurate because the hyperaccurate least squares method and the modified subspace method enable phase retrieval with a small error as shown by the simulations. A MATLAB code, which is used in the experimental section, is provided within the paper to demonstrate its simplicity and easiness. (C) 2016 Optical Society of America.

Visualization of sound field using optical techniques is a powerful tool for understanding acoustical behaviors. It uses light waves to examine the acoustical quantities without disturbing the sound information of the field under investigation. Schlieren imaging is an optical method that uses a camera to visualize the density of transparent media. As it uses a single shot to capture the information without scanning, it can observe both reproducible and non-reproducible sound field. Conventionally, the Schlieren system is applied to high-pressure ultrasound and shock waves. However, since the density variation of air caused by the audible sound field is very small, this method was not applicable for visualizing these fields. In this paper, a spatio-temporal filter bank is proposed to overcome this problem. As the sound is a very specific signal, the spatio-temporal spectrum (in two-dimensional space and time) of the audible sound is concentrated in a specific region. The spatio-temporal filter bank is designed for extracting the sound field information in the specific region and removing noise. The results indicate that the visibility of the sound fields is enhanced by using the proposed method. (C) 2016 Elsevier Ltd. All rights reserved.

Imaging of sound aids the understanding of the acoustical phenomena such as propagation, reflection, and diffraction, which is strongly required for various acoustical applications. The imaging of sound is commonly done by using a microphone array, whereas optical methods have recently been interested due to its contactless nature. The optical measurement of sound utilizes the phase modulation of light caused by sound. Since light propagated through a sound field changes its phase as proportional to the sound pressure, optical phase measurement technique can be used for the sound measurement. Several methods including laser Doppler vibrometry and Schlieren method have been proposed for that purpose. However, the sensitivities of the methods become lower as a frequency of sound decreases. In contrast, since the sensitivities of the phase-shifting technique do not depend on the frequencies of sounds, that technique is suitable for the imaging of sounds in the low-frequency range. The principle of imaging of sound using parallel phase-shifting interferometry was reported by the authors (K. Ishikawa et al., Optics Express, 2016). The measurement system consists of a high-speed polarization camera made by Photron Ltd., and a polarization interferometer. This paper reviews the principle briefly and demonstrates the high-speed imaging of acoustical phenomena. The results suggest that the proposed system can be applied to various industrial problems in acoustical engineering.

In this paper, 3D sound source localization method for simultaneously estimating both direction-of-arrival (DOA) and distance from the microphone array is proposed. For estimating distance, the off-grid problem must be overcome because the range of distance to be considered is quite broad and even not bounded. The proposed method estimates positions based on an extension of the convex clustering method combined with sparse coefficients estimation. A method for constructing a suitable monopole dictionary based on coherence is also proposed so that the convex clustering based method appropriately estimate distance of sound sources. Numerical experiments of distance estimation and 3D localization show possibility of the proposed method.

Nowadays, various types of microphone array are used in many applications. However, it is not easy to compare arrays of different types because each array has been treated by a specific theory depending on the type of an array. Although several criteria have been proposed for microphone arrays for evaluating and/or designing an array, most of them are application-oriented criteria and the best configuration for some criterion may not be a better one in the other criterion. Therefore, an analysis and comparing method for microphone arrays which does not depend on an array configuration and application are necessary. In this paper, infinite-dimensional SVD is proposed for analyzing and comparing properties of arrays. The singular values and functions obtained by proposed method show sampling property of an array and can be unified criterion.

© 2017 The Acoustical Society of Japan. Many acoustical simulation methods have been studied to investigate acoustical phenomena. Modeling of the directivity pattern of a sound source is also important for obtaining realistic simulation results. However, there has been little research on this. Although there has been research on sound source identification, the results might not be in a suitable form for numerical simulation. In this paper, a method for modeling a sound source from measured data is proposed. It utilizes the sum of monopoles as the physical model, and the modeling is achieved by estimating the model parameters. The estimation method is formulated as a convex optimization problem by assuming the smoothness of a solution and the sparseness of parameters. Moreover, an algorithm based on the alternating direction method of multipliers (ADMM) for solving the problem is derived. The validity of the method is evaluated using simulated data, and the modeling result for an actual loudspeaker is shown.

© 2017 Acoustical Society of America. Sound source localization techniques using microphones have been the subject of much interest for many years. Many of them assume far-field sources, and plane waves are used as a dictionary for estimating the direction-of-arrival (DOA) of sound sources. On the other hand, there has been less research on 3D source localization which estimates both direction and distance. In case of estimating distances, monopoles must be used as a dictionary. By setting monopoles in far-field, their waves can be regarded as plane waves, and their distance can be estimated. However, monopoles set at many positions can be impossible due to high computational cost. Moreover, the grid discretization can cause estimation error because there are a lot of the number of grid points in 3D space. Such discretization issue is called off-grid problem. Therefore, a source localization with monopole-only dictionary needs some methods to solve the off-grid problem. The proposed method uses sparse estimation and modified convex clustering with a monopole-only dictionary. Sparse estimation selects the monopoles which are candidates of the source positions. Then, modified convex clustering solves the off-grid problem, and estimates source positions. In this paper, simulation and comparison with another method show effectiveness of the proposed method.

© 2017 Acoustical Society of America. Accurately measuring sound pressure is not an easy task because every microphone has its own mechanical and electrical characteristics. Moreover, the existence of a measuring instrument inside the field causes reflection and diffraction which deform the wavefront of sound to be measured. Ideally, a sensing device should not have any characteristic nor exist inside a measuring region. Although it may sound unrealistic, optical measurement methods are able to realize such ideal situation. Optical devices can be placed outside the sound field, and some of the sensing techniques, which decode information of sound from the phase of light, are able to cancel optical and electrical characteristics. Thus, optical sound measurement methods have possibility of achieving higher accuracy than ordinary sound measurement in principle. However, they have two main drawbacks that have prevented their applications in acoustics: (1) point-wise information cannot be obtained directly because observed signal is spatially integrated along the optical path; and (2) increasing signal-to-noise ratio is difficult because optical measurement of less than a nanometer order is typically required. To overcome the above difficulties, we have proposed several signal processing methods. In this paper, those methods are introduced with the physical principle of optical sound measurement.

© 2017 Acoustical Society of America. Visualization of a sound field helps us to intuitively understand various acoustic phenomena in sound design and education. The most straightforward method is to overlap the measured data onto a photographic image. However, in order to understand an entire three-dimensional (3D) sound field by using a conventional two-dimensional screen, it is necessary to move a camera and measure repeatedly. On the other hand, the augmented reality (AR) techniques such as an video see-through head mounted display (VST-HMD) have been rapidly developed. In this study, we propose a sound field visualization system using an VST-HMD and a hand held four-point microphone. This system calculates sound intensity from the four sound signals in real time. Then, the sound intensity distribution is depicted as arrows in the 3D display. The position and angle of the microphones and users head are acquired via AR markers and head tracking sensors of the VST-HMD. The system realizes simple and effective visualization of 3D sound field information from the various directions and positions of view. For the experiments, the sound fields generated by loudspeakers and motorcycles were visualized. The results suggested that the proposed system can present information of the field in easily recognizable manner.

This paper presents a prototype system of a three-dimensional noise mapping system with an aerial blimp robot. The system's length is 1.5 m, its width is approximately 1.2 m, and its weight is approximately 850 g. The system is divided into two parts
one part is a balloon filled with helium gas, and the other part is a multirotor unit. Since the balloon helps to hover in the air without rotating propellers, the propeller rotation noise can be reduced. The buoyancy of helium gas is lighter than the system weight and therefore the system could return to the ground automatically, even when it is out of control caused by low battery or other problems. The multirotor unit has six propellers, which make enable omnidirectional motion. The multirotor unit also has a system control board with a field programmable gate array system on chip, which integrates central processing unit for controlling of propeller rotation, sound recording, and communicating with the host personal computer. The microphone for recording the sound is mounted at the middle of the balloon, to reduce the effect of propeller rotation noise. We evaluated the system two ways: a comparison of the propeller rotation noises between the system and a general multirotor, and an analysis of acoustical effect of the balloon. The result showed that the propeller rotation noise was reduced by 42 dB as compared with a general multirotor, and the balloon had large effects of the sound field when the balloon was placed between the sound source and the microphone. Finally, we measured the sound pressure level using the proposed system. The result showed that the proposed system can continuously measure sound pressure distribution in noise map space.

© 2017 Acoustical Society of America. Imaging of a sound field aids understanding of the actual behavior of the field. That is useful for obtaining acoustical spatial characteristics of transducers, materials and noise sources. For high spatial resolution imaging, optical measurement methods have been used thanks to its contactless nature. This paper presents sound field imaging method based on parallel phase-shifting interferometry, which enables to acquire an instantaneous two-dimensional phase distribution of light. Information of sound field is calculated from the phase of light based on the acousto-optic theory. The system consists of a polarization interferometer and high-speed polarization camera. The number of the measurement points in a single image are 512 × 512 and the interval between adjacent pixels is 0.22 mm. Therefore, the system can image a sound field with much higher spatial resolution compared with conventional imaging methods such as microphone arrays. The maximum frame rate, which is corresponding to the sampling frequency, is 1.55 M frames per second. This paper contains the principle of optical measurement of sound, the description of the system, and several experimental results including imaging of sound fields generated by transducers and reflection of the sound waves.

Phase extraction methods based on the principal component analysis (PCA) can extract objective phase from phase-shifted fringes without any prior knowledge about their shift steps. Although it is fast and easy to implement, many fringe images are needed for extracting the phase accurately from noisy fringes. In this paper, a simple extension of the PCA method for reducing extraction error is proposed. It can effectively reduce influence from random noise, while most of the advantages of the PCA method is inherited because it only modifies the construction process of the data matrix from fringes. Although it takes more time because size of the data matrix to be decomposed is larger, computational time of the proposed method is shown to be reasonably fast by using the iterative singular value decomposition algorithm. Numerical experiments confirmed that the proposed method can reduce extraction error even when the number of interferograms is small. (C) 2016 Optical Society of America

© 2016, German Acoustical Society (DEGA). All rights reserved. Optical sound measurement, which acquires acoustical quantities by means of optical techniques, is of growing interest as an alternative method for the sound field imaging. There are two remarkable aspects of the optical sound measurement. The first is non-intrusiveness. Since the measurement is achieved by observing the light passed through the sound field, the instruments can be arranged outside the measurement field; non-contact and non-destructive measurement can be achieved. The second one is spatial resolution. Instead of building an array, expanding or scanning of light are often used for the optical imaging. Therefore, the optical imaging does not have the limitation of interval of measurement points due to the size of the instruments as microphone arrays. These two aspects make the optical method possible to image sound field with high spatial resolution and without any disturbance to the original field. In this paper, we show several methods for the optical sound imaging. Laser Doppler vibrometer can be developed as the imaging methods by scanning a narrow light beam. The two dimensional of transient field measurement can be achieved by using a high-speed camera because of single-shot. In addition some signal processing techniques introduced to optical measurement are also described.

For three-dimensional shape measurement, phase-shifting techniques are widely used to recover the objective phase containing height information from images of projected fringes. Although such techniques can provide an accurate result in theory, there might be considerable error in practice. One main cause of such an error is distortion of fringes due to nonlinear responses of a measurement system. In this paper, a postprocessing method for compensating distortion is proposed. Compared to other compensation methods, the proposed method is flexible in two senses: (1) no specific model of nonlinearity (such as the gamma model) is needed, and (2) no special calibration data are needed (only the observed image of the fringe is required). Experiments using simulated and real data confirmed that the proposed method can compensate multiple types of nonlinearity without being concerned about the model. (C) 2016 Optical Society of America

Sound-field imaging, the visualization of spatial and temporal distribution of acoustical properties such as sound pressure, is useful for understanding acoustical phenomena. This study investigated the use of parallel phase-shifting interferometry (PPSI) with a high-speed polarization camera for imaging a sound field, particularly high-speed imaging of propagating sound waves. The experimental results showed that the instantaneous sound field, which was generated by ultrasonic transducers driven by a pure tone of 40 kHz, was quantitatively imaged. Hence, PPSI can be used in acoustical applications requiring spatial information of sound pressure. (C) 2016 Optical Society of America

The windowed Fourier filtering (WFF), defined as a thresholding operation in the windowed Fourier transform (WFT) domain, is a successful method for denoising a phase map and analyzing a fringe pattern. However, it has some shortcomings, such as extremely high redundancy, which results in high computational cost, and difficulty in selecting an appropriate window size. In this paper, an extension of WFF for denoising a wrapped-phase map is proposed. It is formulated as a convex optimization problem using Gabor frames instead of WFT. Two Gabor frames with differently sized windows are used simultaneously so that the above-mentioned issues are resolved. In addition, a differential operator is combined with a Gabor frame in order to preserve discontinuity of the underlying phase map better. Some numerical experiments demonstrate that the proposed method is able to reconstruct a wrapped-phase map, even for a severely contaminated situation. (C) 2016 Optical Society of America

Recent development of microphone arrays which consist of more than several tens or hundreds microphones enables acquisition of rich spatial information of sound. Although such information possibly improve performance of any array signal processing technique, the amount of data will increase as the number of microphones increases; for instance, a 1024 ch MEMS microphone array, as in Fig. 1, generates data more than 10 GB per minute. In this paper, a method constructing an orthogonal basis for efficient representation of sound data obtained by the microphone array is proposed. The proposed method can obtain a basis for arrays with any configuration including rectangle, spherical, and random microphone array. It can also be utilized for designing a microphone array because it offers a quantitative measure for comparing several array configurations.

In this study, we observe traveling sound waves with a laser and computed tomography. In our previous research, we observed steady-state sound fields using a sine wave signal. However, transient sound fields observation is necessary in order to observe more complicated sound fields that need to be separated into direct and reflected sounds. Therefore, in this study, we use a traveling sound wave (pulse sound wave). For fundamental experiments, we observed projections of a traveling pulse sound wave generated by a 2-way loudspeaker and a flat-panel loudspeaker with a laser. For transit sound fields, we used the sound field projections obtained with a laser to observe that a flat sound wave generated by a flat-panel loudspeaker is reflected by a sound-reflecting board. Then, we reconstructed the sound field information on the transition of a pulse sound wave generated by a 2-way loudspeaker, by computed tomography.

Visualization of sound field using Schlieren technique provides many advantages. It enables us to investigate the change of the sound field in real-time from every point of the observing region. However, since the density gradient of air caused by the disturbance of acoustic field is very small, it is difficult to observe the audible sound field from the raw Schlieren video. In this paper, to enhance visibility of the audible sound fields from the Schlieren videos, we propose to use spatio-temporal filters for extracting sound information and for noise removal. We have utilized different filtering techniques such as the FIR bandpass filter, the Gaussian filter, the Wiener filter and the 3D Gabor filter, to do this. The results indicate that the data observed after using these signal processing methods are clearer than the raw Schlieren videos.

Visualization is an effective way to understand the behavior of a sound field. There are several methods for such observation including optical measurement technique which enables a non-destructive acoustical observation by detecting density variation of the medium. For audible sound propagating through the air, however, smallness of the variation requires high sensitivity of the measuring system that causes problematic noise contamination. In this paper, a method for reconstructing two-dimensional audible sound fields from noisy optical observation is proposed.

A method for reconstructing a measured sound field using the Kirchhoff-Helmholtz boundary integral equation is presented. L4-norm ball shape was chosen for the boundary, which is smooth and more suitable for data measured along the rectangular coordinate than the circle. ADMM (alternating direction method of multipliers) was employed to solve the initial value estimation via sparsity and the norm ball constrained least squares problem. The experiment using synthetic data confirmed the effectiveness of the method.

A study is conducted to propose a sparse representation method for acoustic signals by the use of curvelets, and confirm its efficacy through an example of speech denoising. The curvelet denoising method was applied using the hard thresholding to speech, to demonstrate the effectiveness of the proposed representation. The method was applied to a female speech with additive pink noise for conducting the investigations. The level of the noise was chosen so that signal-to-noise ratio (SNR) became 10 dB. The thresholding process was iterated 10 times. The same input signal was processed by two denoising Methods for comparison.

Light propagating through a sound field is affected by variations in the density of the medium caused by sound. Therefore, acoustical measurements using light have been studied. The popular measurement methods use the phase shift of the transmitted light. Because they detect integrated acoustical quantities along the optical path of the detected light, time and effort are required to measure the quantities at a single point. On the other hand, single-point acoustical particle velocity measurement by light scattering has been proposed. Using light scattering enables the measurement of non-integrated quantities because the scattered light includes only the acoustical information at a scattering point. However, a method of non-invasive sound pressure measurement at a single point in a free field has not been established. This paper proposes sound pressure measurement at a scattering point, in which the light scattered by particles in the sound field is observed. The intensity of light scattered in the sound field indicates the sound pressure because the intensity of the scattered light is proportional to the density of scatterers. The theory of light scattering by sounds is formalized, and sound measurement experiments with light scattering are also conducted using water drops and air particles as scatterers.

Small highly efficient ultrasonic transducers are in high demand to fabricate compact parametric speakers. We focus on small piezoelectric transducers that can be used for ultrasonic emitters of parametric speakers. Typical small piezoelectric transducers have piezoelectric boards and radial cones. We propose a transducer consisting of a unimorph diaphragm and a flat metal plate. This structure gives two resonant peaks, which are determined by the physical parameters and dimensions of the diaphragms, the flat plate, and their junction structure. Controlling these resonant peaks is one approach to fabricating transducers having the ideal frequency response of the sound pressure for parametric speakers. We devised a design to control these two resonant peaks by adjusting the junction structure of the diaphragm and the flat plate. Using the results of a theoretical analysis, we designed an improved transducer that satisfies the ideal frequency response for parametric speakers.

We investigated a new communication-aid system focused on bone-conduction through a tooth, for listening to and recording voices. In this paper, we developed a tooth-conduction microphone (TCM) and evaluate the articulation of tooth-conducted voice (TCV). Because the TCM has the shape of one's dental mold, it is wearable like a mouthpiece. Moreover, it can extract tooth vibration during phonation as TCV. To evaluate articulation of TCV, we adopted monosyllable articulation for subjective assessment and linear predictive coding cepstral distance for objective assessment. The results of articulation show that TCV is not sufficiently clear compared to airconducted. However, it is confirmed that TCV is robust to environmental noise because the accuracy rate is not decreased when the TCV is recorded under high ambient noise.

One possible solution for generating point sound sources in mid air is the photoacoustic effect: energy transduction from light energy to sound energy. The photoacoustic effect generates sounds from the alternate current components of air expansion due to the heat generated by light absorption of a material when light modulated with acoustic signal is radiated to a material. In order to confirm sound reproduction using the photoacoustic effect, the experiments to reproduce a pure tone and a musical sound is performed. In order to generate louder sound, the light from the halogen lamp is focused on a charcoal, which has high absorptive power since a charcoal is black and spongy. It is shown that a halogen lamp can be modulated with acoustic signal although the amplitude of higher frequency components is reduced because of the response speed of halogen lamp. Next, the experiments of sound reproduction using a halogen lamp and a charcoal were performed.

An effective way to understand the behavior of a sound field is to visualize it. An optical measurement method is a suitable option for this as it enables contactless non-destructive measurement. After measuring a sound field, interpolation of the data is necessary for a smooth visualization. However, conventional interpolation methods cannot provide a physically meaningful result especially when the condition of the measurement causes moire effect. In this paper, a special interpolation method for an optically visualized sound field based on the Kirchhoff-Helmholtz integral equation is proposed.

A Yagi-Uda antenna gets high directivity by applying current phase shift between elements due to resonance phenomena. It has some directors and reflectors, which are elements without electric supply. The length of directors is shorter than half-wave and that of reflectors is longer than half-wave. We proposed an acoustic Yagi-Uda antenna which elements are resonance tubes and a loudspeaker. The aim of this research is to im- prove directivity in a specific frequency. This can be applied to Radio Acoustic Sounding System (RASS), which is a kind of radar for weather observation, or to a parametric loudspeaker. The phase shift of sound waves was observed in the condition with a resonance tube and without the tube at the same position. That shift changes suddenly around the resonance frequency of the tube. Our acoustic antenna has resonance tubes that have different length as directors and reflectors to apply this phenomenon. Moreover, the distances be- Tween a loudspeaker and tubes were concerned by some experiments and by numerical analysis. The acoustic antenna showed directivity in an appropriate condition of the distances and the frequency of the sound source. It will be also added the consideration about the effective frequency band of this acoustic antenna.

With the aim of making speech easier to listen to on a TV receiver. We are researching effective ways of combining speech enhancement techniques and background sound suppression techniques so as to adapt to the characteristics of the sound in programs and perform gain-control only on the speechless intervals. The preparatory evaluation tests confirm that it is possible to 6dB reduce program background volume by the proposed method. The results of evaluation tests using broadcast-program sound showed that a prototype device was able to adjust a suitable level of background sound for elderly people.

Piezoelectric actuators are used in a wide range of electrical devices, including piezoelectric speakers, buzzers, haptics and ultrasonic transducers. For piezoelectric actuator systems used in mobile devices, the most important issue is improving the electromechanical conversion efficiency. The power consumed by the actuators must be minimized due to the small size of the batteries used. The frequency response around the mechanical resonance must be carefully designed to enable low power driving. The resonant frequencies of piezoelectric actuators that consist of integrated components, such as the metal cones in ultrasonic speakers, are determined by the energy dispersion of the total system. Therefore, factors such as the size and physical properties of each component must be designed to optimize the resonant frequencies for practical applications. The total energy of the piezoelectric system is described by Lagrange-Maxwell equations. Even though it is not easy to solve the differential equations written in a Lagrangian coordinate system by using exact calculations, useful information for designing systems can be derived from approximate calculations. In this paper, we will introduce design guidelines that can be used to optimize the resonant frequencies of piezoelectric actuators with integrated components, based on analysis using the Lagrangian coordinate system. © 2013 Acoustical Society of America.

It is highly important to generate a point sound source in mid air for several applications such as virtual realty and precise acoustic measurement since most of acoustic theories are based on a point sound source. One possible solution for generating a point sound source in mid air is the photoacoustic effect that generates sounds from the alternate-current components of air expansion due to the heat generated by light absorption of a material when light modulated with acoustic signal is radiated to a material. To apply this method to molecule of gases in mid air, it is possible to generate a point sound source in mid air. Thus, for the first step to realize this possibility, this paper attempt to confirm that it is possible to generate audible sounds using the photoacoustic effect. In particular, this paper describes the sound generation using a charcoal that has high absorptive power and a halogen lamp that can produce high intensity infrared light, which is easier, absorbed by gas molecules than visible light. © 2013 Acoustical Society of America.

One common problem of outdoor recordings is a contamination of wind noise which has highly non-stationary characteristics. Although there are a lot of noise reduction methods which work well for general kinds of noises, most methods perform worse for wind noise due to its non-stationary nature. Therefore, wind noise reduction need specific technique to overcome this non-stationary. Empirical mode decomposition (EMD) is a relatively new method to decompose a signal into several data-driven bases which are modeled as amplitude and frequency modulated sinusoids that represent wind noise better than quasi-stationary analysis methods such as short-time Fourier transform since it assumes an analyzing signal as non-stationary. Thus, EMD has a potential to reduce wind noise from recorded sounds in an entirely different way from ordinary methods. In this paper, the method to apply EMD as a wind noise suppressor is presented. The experiment is performed on a female speech superimposed with wind noise, and the results showed its possibility. © 2013 Acoustical Society of America.

Conversation is one of the most important channels for human beings. To help communications, speech recognition technologies have been developed. Above all, in a conversation, not only contents of utterances but also intonations and tones include important information regarding a speaker's intention. To study the sphere of human speech, microphones are typically used to record voices. However, since microphones have to be set around a space, their existences affect a physical behavior of the sound field. To challenge this problem, we have suggested a recording method using a high-speed camera. By using a high-speed camera for recording sound vibrations, it can record two or more points within the range of the camera at the same time and can record from a distance, without interfering with the sound fields. In this study, we extract voice information using high-speed videos which capture both a face and a cervical part of the subject. This method allows recording skin vibrations which contain voices with individuality and extrapolating sound waves by using an image processing method. The result of the experiment shows that a high-speed camera is capable of recording voice information. © 2013 Acoustical Society of America.

Since bone-conducted sound is conveyed to cochlea directly, without passing through eardrum, it is audible even for hard-of-hearing people whose inner ears are still normal. In this study, we utilize bone-conducted sound via teeth so as to support sound communication. We implemented a bone-conducted actuator on teeth, while actuators of prevalent hearing aids are attached to mastoid, forehead or jaw in general. Teeth convey sound excitation more easily, because they are bare bones, not covered with skin. Our communication aid is made in the form of mouthpiece with a dental material, and it can be readily put on and taken off from a tooth. Using this actuator, we attempted to record vibrations of teeth when a subject produces a sound. In addition, we carried out experiments regarding sound lateralization of bone-conducted sound via teeth with this actuator. The result shows that examinees can perceive right and left using bone-conducted sound via teeth. The aim of this study is to suggest a new communication aid system not only for hard-of-hearing people but also for the robust. © 2013 Acoustical Society of America.

This study is a report of the result of investigating the sound environment at setting childcare scene in nursery institutions focused on children's learning activity aiming to make the acoustic environment as their learning field. By the behavioral observation and the sound field analysis at activity scene, we observed the characteristic of sound field at each study scene and the change of the acoustic environment when the teacher was setting the learning environment.The result shows that the sound by the children's behavior was a keynote source at dynamic activity scene like singing and dancing. Especially, the level of 1-2kHz band by children's voice and low frequency sound was characteristic. And for making settled space that was attached weight in young children's educational field, teachers often used the sound factor by the setting environment scene and a moderate silence was a very important environmental factor. For acoustic design according to the educational purpose, many-sided investigation of the sound space was essential to understand the teacher's setting behavior and children's behavioral pattern.

In this paper, we propose a measuring method of the sound field from high-speed movie of dust. The movements of dust in the sound field are affected by the sound vibration. We observe the dust using high-speed cameras. The movie is recorded by one high-speed camera in order to get the information of 2-D sound field and two high-speed cameras for 3-D. The influence of air current is reduced from the movement of dust so that the sound field information is extracted. The experimental results indicate that this method is effective to observe the sound field especially composed of low frequency components.

With the aim of making speech easier to listen to on a TV receiver, a noble method for back-ground-sound suppression processing was proposed, and the results of evaluation tests using broadcast-program sound showed that a prototype device was able to adjust a suitable level of background sound for elderly people. Our proposed method was able to suppress the magnitude of sound components with low correlation by using 2ch stereo signals and perform gain-control only on the speechless intervals. The preparatory evaluation tests confirm that it is possible to suitably reduce program background volume by the proposed method. On the basis of this result, a device for suppressing background sound by decoding the transport stream (TS) of a broadcast program was prototyped. The results of evaluation tests using this device demonstrate that the magnitude of background sound can be adjusted to a suitable level for elderly people.

A measuring method of the sound field using a high-speed movie of dust was proposed. A sound field generated using two speakers was measured from high-speed movies of dust. Two high-speed cameras and the powered monitor speakers were located. Speaker-L was driven by the sound of Japanese drums and Speaker-R was driven by 80 Hz sinusoidal sound. To analyze the frequency component, generalized harmonic analysis (GHA) was used. From the result of the waveforms and the frequency components, it is confirmed that the sound field information can be obtained from the movement of dust.

A study was conducted to demonstrate the design guidelines to use the multiband compressor as the suppressor of the electrical power for piezoelectric speakers. The design guidelines stated that the driving system needed to be designed according to signals whose energy concentrated in high frequency band, as electrical admittance of the piezoelectric speakers increased along with power consumption in high frequency band. The performance of the proposed system was investigated and the cutoff frequency of high pass and low pass filters and parameter of compressor were optimized to satisfy two requirements, such as high frequency components of standard signal, which needed to go through without any suppression and energy of high frequency band needed to be suppressed without exceeding the maximum rating of the driving system when it was excess. The response in time domain needed to be calculated as the solution of ordinary differential equations for the equivalent circuit for accurate estimation.

The use of the bread slicing method to reduce the amount of communication among nodes of a computer cluster on parallel computing of the distributed memory system, was investigated. The computer cluster consisted of 128 calculating nodes were used for the study. The sound wave in a three dimensional sound field was used to determine nodes distance. Boundary conditions was used to calculate sound pressure at grid points. The 256 GB memory space of the cluster was used for dividing the calculating field. The calculation of the sound field was performed using a spatial grid that is effective to calculate field with less memory space. The field was divided by the bread slicing method that requires a shorter communicating time among the processes. The method has the ability to increase the speed and scale of a distributed memory system.

The method for estimating the direction of arrival (DOA) using a matching pursuit algorithm under reverberant conditions is discussed. The method starts with the obtaining of an array output of the delay-and-sum method and calculating the average array output in the fixed frequency range. The DOA is estimated by iteration at each step and a re-optimization of all DOA found at the earlier steps. It is suggested that the method can be improved by considering the spatial information from this method.

In this paper, we describe some new sound field measurement methods by using laser Doppler vibrometer (LDV). By Irradiating the reflection wall with a laser, we can observe the light velocity change that is caused by the refractive index change from the change in air density. It means that it is possible to observe the change of the sound pressure.
We measured a sound field projection on a 2-D plane using a scanning laser Doppler vibrometer (SVM) which can visualize a sound field. And we made a 3-D sound field reconstruction from some 2-D laser projections based on the computed tomography (CT) techniques. We made the reconstruction image for the sound field near the loudspeaker or in the room.

In this paper, we describe a new source separation method in which uses spatial information derived from the direction of arrival (DOA) estimates of each direct and reflected sound issued. The method we propose has the following steps: (1) each DOA is estimated using matching pursuit and reoptimized after each new DOA is estimated, (2) using these DOA estimates, the mixing matrix is also estimated and the inverse of the mixing matrix is used to separate the mixture signals. In our experiments, we obtained a better signal separation with the new method than with the conventional frequency-domain independent component analysis (ICA)-based source separation method.

The sound field reproduction has been studied by many people. Dr. Itow suggested the stereophonies and an analyze the two channels system. We extend this theory and suggest the sound field control and reproduction method by wave front synthesis considering human hearing sense. We explain the stereophonies system and multi speakerphones system. Then we simulate this system and make sure of its effect. We are able to construct the virtual reality system, which has a realizable number of speakerphones.

Reverberation time, distribution of sound pressure, intelligibility, and/or other parameters are used in sound room evaluation. But characteristics of room acoustics are complex, and often quite different impressions are received from rooms that have nearly the same parameters. These differences might come from the difference of spatial information, especially in early reflection periods. Thus a four‐microphone method is proposed to measure spatial information of the room. Here, the sound field reproduction using the wavefront synthesis [A. J. Berkhout, J. Acoust. Soc. Am. 93(5) (1993) and Y. Yamasaki, J. Acoust. Soc. Jpn. 10(2) (1989)] based on the four‐point measurement is discussed. © 1996, Acoustical Society of America. All rights reserved.