An informative acoustic-feature-selection method for collecting target sources in noisy environments is proposed. Wiener filtering is a powerful framework for sound-source enhancement. For Wiener-filter estimation, statistical-mapping functions, such as deep neural network based or Gaussian mixture model based mappings, have been used. In this framework, it is essential to find informative acoustic features that provide effective cues for Wiener-filter estimation. In this study, we measured the informativeness of acoustic features using mutual information between acoustic features and supervised Wiener-filter parameters, e.g., prior signal-to-noise ratios, and developed a method for automatically selecting informative acoustic features from a large number of feature candidates. To automatically select optimum features, we derived a differentiable objective function in proportion to mutual information based on the kernel method. Since the higher order correlations between acoustic features and Wiener-filter parameters are calculated using the kernel method, the statistical dependence of these variables is accurately calculated; thus, only meaningful acoustic features are selected. Through several experiments conducted on a mock sports field, we confirmed that the signal-to-distortion ratio score improved when various types of target sources were surrounded by loud cheering noise.

We investigated informative acoustic feature extraction based on dimension reduction for collecting target sources on a noisy sports field. Although a Wiener filter is often used for sound source enhancement, it is difficult to accurately design the Wiener filter by simply using spatial cues because the noise on a sports field (e.g., cheering from spectators) arrives from the same direction as that of the targeted source. A statistical approach is used to estimate the Wiener filter by using pre-trained acoustic feature models. However, an informative acoustic feature, which provides a powerful clue for clear extraction of the target source, is unknown. For this study, we developed a method for optimizing a projection matrix for dimension reduction by maximizing the mutual information between acoustic features and the Wiener filter. Through experiments using two-directional microphones on a mock sports field, we confirmed that the proposed method outperformed previous methods in terms of both the noise reduction and quality of the recovered sound sources.

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 are only known as the desired sound field; therefore, SP-DS conversion algorithms are necessary. Current SP-DS conversion methods do not take into account sound sources to be reproduced, which results in severe spatial aliasing artifacts. Our proposed method decomposes the received sound pressure distribution based on the generative model of the sound field. Numerical simulation results indicate that the proposed method can achieve higher reproduction accuracy compared to the current methods, especially in higher frequencies above the spatial Nyquist frequency.

A novel short-time Fourier transform (STFT) domain adaptive filtering scheme is proposed that can be easily combined with nonlinear post filters such as residual echo or noise reduction in acoustic echo cancellation. Unlike normal STFT subband adaptive filters, which suffers from aliasing artifacts due to its poor prototype filter, our scheme achieves good accuracy by exploiting the relationship between the linear convolution and the poor prototype filter, i.e., the STFT window function. The effectiveness of our scheme was confirmed through the results of simulations conducted to compare it with conventional methods.

Massive multichannel sound reproduction is necessary for highly immersive full-duplex communication. Efficient echo cancellation between massive loudspeakers and microphones is indispensable, and wave-domain adaptive filtering reduces the computational complexity drastically. We propose to further reduce this complexity by exploiting the band-limited property that the sound field has in the space-time-frequency representation. Experimental evaluations support the applicability of the proposed method.

This paper describes an ITU-T G.711 embedded wideband speech coder, submitted as a candidate to the ITU-T G.711 wideband extension standardization qualification phase. The codec generates a bitstream comprised of three layers: a G.711 core layer with noise shaping, a time-domain weighted vector quantized narrowband enhancement layer, and an MDCT-based higher band enhancement layer. Through subjective evaluations, the coder was found to meet all tested requirements and objectives set in terms of reference, with a low computational complexity at 10 WMOPS.

Low-cost highly-efficient speech coding is important for personal multimedia communications. In this paper we propose a new low-complexity speech coding method called "Dual-Pulse CS-CELP (DP-CS-CELP)" at 7.8 kbit/s. This method is based on ITU-T G.729. To reduce the complexity, we applied a new excitation model to the random code vectors and simplified the LPC coding, adaptive codebook search, perceptual weighting, and the other structures. The number of operations for this encoder is 3.80 MOPS, which achieves real-time speech coding and decoding on personal computers. Although the efficiency of this coder is a little lower than that of G.729, the MOS listening test showed that the subjective quality was equivalent to or a little better than that of G.726 (32-kbit/s ADPCM).

This paper describes the design of a speech coder called pitch synchronous innovation CELP (PSI-CELP) for low hit-rate mobile communications. PSI-CELP is based on CELP, but has more adaptive excitation structures. In voiced frames, instead of conventional random excitation vectors, PSI-CELP converts even the random excitation vectors to have pitch periodicity by repeating stored random vectors as well as by using an adaptive codebook, in silent, unvoiced, and transient frames, the coder stops using the adaptive codebook and switches to fixed random codebooks. The PSI-CELP coder also implements novel structures and techniques: an FIR-type perceptual weighting filter using unquantized LPC parameters, a random codebook with a conjugate structure trained to be robust against channel errors, codebook search with delayed decision, a gain quantization with sloped amplitude, and a moving average prediction coding of LSP parameters, Our speech coder is implemented by DSP chips. Its coded speech quality at 3.6 kb/s with 2.0 kb/s redundancy is comparable to that of the Japanese full-rate VSELP coder at 6.7 kb/s with 4.5 kb/s redundancy. The basic structure of this PSI-CELP coder has been chosen as the Japanese half-rate speech codec for digital cellular telecommunications.>

This paper proposes high-quality and low bit-rate (3.6 and 2.4 kbit/s) coders using a pitch synchronous innovation CELP (PSI-CELP) method or a phase adaptive PSI-CELP. PSI-CELP, which is used as the excitation structure of the half-rate codec for the standard of Japanese digital mobile telephony, is based on CELP but adds pitch synchronous innovation, which means that even random codevectors are adaptively converted to have pitch periodicity for voiced frames. Phase adaptive PSI-CELP makes not only the periodicity, like in PSI-CELP, but also the phase of random codevectors equal to those of an adaptive codevector. The subjective qualities of the 3.6- and 2.4-kbit/s coders exceed those of the 6.7-kbit/S VSELP coder, which is the full-rate codec for the standard of Japanese digital mobile telephony, and-the 4.8-kbit/s U.S. Federal Standard 1016 CELP coder, respectively, in the error-free condition.>