14 accepted papers
Jointly training a speech enhancement (SE) front-end and an automatic speech recognition (ASR) back-end has been investigated as a way to mitigate the influence of processing distortion generated by single-channel SE on ASR. In this paper, we investigate the effect of such joint training on the sign…
Array processing performance depends on the number of microphones available. Virtual microphone estimation (VME) has been proposed to increase the number of microphone signals artificially. Neural network-based VME (NN-VME) trains an NN with a VM-level loss to predict a signal at a microphone locati…
We address the problem of separating moving sources using online independent vector analysis (IVA). To solve this problem, researchers have extended the iterative projection (IP) and iterative source steering (ISS) algorithms developed for batch auxiliary-function-based IVA (AuxIVA) to online scenar…
Weighted prediction error (WPE) is a fundamental dereverberation method to predict the late reverberation component of an observed signal based on linear prediction (LP). Recently, WPE was extended to Switching WPE (SwWPE), which optimizes (i) multiple LP filters and (ii) switching parameters to det…
Full-rank spatial covariance analysis (FCA) is a blind source separation (BSS) method, and can be applied to underdetermined cases where the sources outnumber the microphones. This paper proposes a new extension of FCA, aiming to improve BSS performance for mixtures in which the length of reverberat…
This paper proposes an approach for optimizing a Convolutional BeamFormer (CBF) that can jointly perform denoising (DN), dereverberation (DR), and source separation (SS). First, we develop a blind CBF optimization algorithm that requires no prior information on the sources or the room acoustics, by…
This paper presents a new low-latency online blind source separation (BSS) algorithm. Although algorithmic delay of a frequency domain online BSS can be reduced simply by shortening the short-time Fourier transform (STFT) frame length, it degrades the source separation performance in the presence of…
Developing microphone array technologies for a small number of microphones is important due to the constraints of many devices. One direction to address this situation consists of virtually augmenting the number of microphone signals, e.g., based on several physical model assumptions. However, such…
Recent studies have shown that acoustic beamforming using a microphone array plays an important role in the construction of high-performance automatic speech recognition (ASR) systems, especially for noisy and overlapping speech conditions. In parallel with the success of multichannel beamforming fo…
In this paper, we address a blind source separation (BSS) problem and propose a new extended framework of independent positive semidefinite tensor analysis (IPSDTA). IPSDTA is a state-of-the-art BSS method that enables us to take interfrequency correlations into account, but the generative model is…
In this article, we investigate an integrated mask-based convolutional beamforming method for performing simultaneous denoising, dereverberation, and source separation. Conventionally, it is difficult for neural network-supported mask-based source separation to perform denoising and dereverberation…
We address the convolutive blind source separation problem for the (over-)determined case where (i) the number of nonstationary target-sources K is less than that of microphones M, and (ii) there are up to M - K stationary Gaussian noises that need not to be extracted. Independent vector analysis (I…
This paper presents a novel heterogeneous-input multi-channel acoustic model (AM) that has both single-channel and multi-channel input branches. In our proposed training pipeline, a single-channel AM is trained first, then a multi-channel AM is trained starting from the single-channel AM with a rand…
Independent low-rank matrix analysis (ILRMA), a unified method of independent vector analysis (IVA) and nonnegative matrix factorization (NMF), is a state-of-the-art blind source separation method for convolutive mixtures. Although ILRMA provides high separation performance for music signals whose s…