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Sparse representations of sound fields have become popular in various acoustic inverse problems. The simplest models assume spatial sparsity, where a small number of sound sources are located in the near-field. However, the performance of these models deteriorates in the presence of strong reverberation. To properly treat the reverberant components, we introduce three types of reverberation models:...
We propose a sound field decomposition method that takes into consideration spatio-temporal sparsity. It has been proved that sparse representation of a sound field is effective in reducing errors originating from spatial aliasing artifacts compared with conventional plane wave decomposition. In most current methods of sparse sound field decomposition, the spatial sparsity of the sound source distribution...
A sound field reproduction method that exploits prior information on listening areas is proposed. Most current methods are aimed at reproducing the sound field over the entire space or around listener locations. We formulate the objective function for this problem as the expectation minimization of the spatial squared error of the sound pressure inside the listening areas. The optimal driving signals...
A sound field reproduction method using prior information on listening areas is proposed. Most current methods aim to reproduce the sound field over the entire space or around the listener's location. The methods considering the location of listening areas enable high reproduction accuracy with a small number of loudspeakers inside these areas; however, the reproduction accuracy outside these areas...
We address a novel nonnegative matrix factorization (NMF) with a new basis deformation method to handle various music sounds. Conventional supervised NMF has a critical problem that a mismatch between bases trained in advance and an actual target sound reduces the accuracy of separation. To solve this problem, we proposed an advanced supervised NMF that applies a single time-invariant filter to the...
In this paper, we address the music signal separation problem and propose a new supervised nonnegative matrix factorization (SNMF) algorithm employing the deformation of a spectral supervision basis trained in advance. Conventional SNMF has a problem that the separation accuracy is degraded by a mismatch between the trained basis and the spectrogram of the actual target sound in open data. To reduce...
Source separation using an ad hoc microphone array can be useful for enhancing speech in such applications as teleconference systems without the need to prepare special devices. However, the positions of the sources (and the microphones when using an ad hoc microphone array) can change during recording, thus violating the commonly made assumption in many source separation algorithms that the mixing...
A sparse sound field decomposition method using prior information on source signals in the time-frequency domain is proposed. Sparse sound field decomposition has been proved to be effective for various acoustic signal processing applications. Current methods for sparse decomposition are based only on the spatial sparsity of the source distribution. However, it can be assumed that possible source...
Multichannel non-negative matrix factorization based on a spatial covariance model is one of the most promising techniques for blind source separation. However, this approach is not tractable for a large number of microphones, M, because the computational cost is of order O(M3) per time-frequency bin. To circumvent this drawback, we propose non-negative tensor factorization in the wavenumber domain,...
A sound field decomposition method for a reverberant environment is proposed. Sound field decomposition is the foundation of various acoustic signal processing applications and enables the estimation of the entire sound field from pressure measurements. Although spatial Fourier analysis of the sound field has been widely used, sparse decomposition of the sound field has recently been proved to be...
A method for sparse sound field decomposition with parametric dictionary learning is proposed. Sound field decomposition forms the foundation of various acoustic signal processing applications. Our main focus is sound field recording and reproduction for high-fidelity audio systems. To improve the reproduction accuracy above the spatial Nyquist frequency, determined by the intervals between array...
A sparse sound field decomposition method is proposed. Sound field decomposition is the foundation of the various acoustic signal processing applications and enables the estimation of the entire sound field from pressure measurements. The plane wave decomposition, i.e., spatial Fourier analysis, of the sound field has been widely used; however, artifacts originating from spatial aliasing occur above...
A sound field recording and reproduction method for spherical arrays that takes into account prior information on the locations of sound sources to be reproduced, i.e., primary sources, is proposed. Current methods using spherical arrays of microphones and loudspeakers, such as higher order ambisonics (HOA), are based on sound field analysis and synthesis in a spherical harmonic domain. However, the...
A method for achieving super-resolution of sound field recording and reproduction is proposed. To obtain driving signals of loudspeakers for reproduction from received signals of microphones, sparse signal decomposition makes it possible to reduce spatial aliasing artifacts when the number of microphones is less than that of loudspeakers. For more accurate and robust signal decomposition, we propose...
This paper addresses a new statistical model of binaural signals and its application to efficient binaural source separation. Binaural source separation is always required to retain a spatial cue of the separated sound, such as a head-related transfer function (HRTF). However, the direct use of an HRTF is not realistic because this information is normally not known in advance. To cope with this problem,...
We propose an efficient method for measuring impulse responses between linear arrays of loudspeakers and microphones with a spatio-temporal stretched pulse (STSP). We derived the STSP by extending a time-stretched pulse (TSP) to the spatial domain; therefore, an STSP is a signal whose temporal and spatial frequencies simultaneously increase with time. When M denotes the number of array elements, the...
We propose a novel close-talking spherical microphone array that uses the residual signal between the observed sound pressure and the interpolated sound pressure at the center of the spherical array. The interpolated sound is obtained from the sound pressures observed on the surface of a sphere on the basis of the spherical harmonic expansion, assuming that the sound originates from the outside of...
We propose a sound-pressure-to-driving-signal (SP-DS) conversion method for sound field reproduction based on sparse sound field representation. The most important problem in sound field reproduction is how to calculate driving signals of loudspeakers to reproduce desired sound fields. In common recording and reproduction systems, sound pressures at multiple positions obtained in a recording area...
Sound field reproduction methods calculate driving signals of loudspeakers to reproduce the desired sound field. In common recording and reproduction systems, sound pressures at multiple positions obtained in a recording room are only known as the desired sound field; therefore, signal transformation algorithms from sound pressures into driving signals (SP-DS conversion) are necessary. Although several...
For with-height reproduction of a sound field, an efficient technique is to record and reproduce the sound field at lower resolution at an elevation angle than that at a horizontal angle based on auditory perception. To achieve this, developing a method using multiple horizontal linear arrays of microphones and loudspeakers is necessary. We propose a sound field reproduction method for a cylindrical...
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