137 citations · 221 across the 13 of their papers we have counts for
9 papers · 1 filter
SHAMaNS: Sound Localization with Hybrid Alpha-Stable Spatial Measure and Neural Steerer
Diego Di Carlo, Mathieu Fontaine, Aditya Arie Nugraha +2
This paper describes a sound source localization (SSL) technique that combines an -stable model for the observed signal with a neural network-based approach for modeling steerin…
Run-Time Adaptation of Neural Beamforming for Robust Speech Dereverberation and Denoising
Yoto Fujita, Aditya Arie Nugraha, Diego Di Carlo +3
This paper describes speech enhancement for realtime automatic speech recognition (ASR) in real environments. A standard approach to this task is to use neural beamforming that can…
Neural Fast Full-Rank Spatial Covariance Analysis for Blind Source Separation
Yoshiaki Bando, Yoshiki Masuyama, Aditya Arie Nugraha +1
This paper describes an efficient unsupervised learning method for a neural source separation model that utilizes a probabilistic generative model of observed multichannel mixtures…
Generalized Fast Multichannel Nonnegative Matrix Factorization Based on Gaussian Scale Mixtures for Blind Source Separation
Mathieu Fontaine, Kouhei Sekiguchi, Aditya Nugraha +2
This paper describes heavy-tailed extensions of a state-of-the-art versatile blind source separation method called fast multichannel nonnegative matrix factorization (FastMNMF) fro…
Self-supervised Neural Audio-Visual Sound Source Localization via Probabilistic Spatial Modeling
Yoshiki Masuyama, Yoshiaki Bando, Kohei Yatabe +3
Detecting sound source objects within visual observation is important for autonomous robots to comprehend surrounding environments. Since sounding objects have a large variety with…
Deep Bayesian Unsupervised Source Separation Based on a Complex Gaussian Mixture Model
Yoshiaki Bando, Yoko Sasaki, Kazuyoshi Yoshii
This paper presents an unsupervised method that trains neural source separation by using only multichannel mixture signals. Conventional neural separation methods require a lot of…
Unsupervised Speech Enhancement Based on Multichannel NMF-Informed Beamforming for Noise-Robust Automatic Speech Recognition
Kazuki Shimada, Yoshiaki Bando, Masato Mimura +3
This paper describes multichannel speech enhancement for improving automatic speech recognition (ASR) in noisy environments. Recently, the minimum variance distortionless response…
Fast Multichannel Source Separation Based on Jointly Diagonalizable Spatial Covariance Matrices
Kouhei Sekiguchi, Aditya Arie Nugraha, Yoshiaki Bando +1
This paper describes a versatile method that accelerates multichannel source separation methods based on full-rank spatial modeling. A popular approach to multichannel source separ…
Statistical Speech Enhancement Based on Probabilistic Integration of Variational Autoencoder and Non-Negative Matrix Factorization
Yoshiaki Bando, Masato Mimura, Katsutoshi Itoyama +2
This paper presents a statistical method of single-channel speech enhancement that uses a variational autoencoder (VAE) as a prior distribution on clean speech. A standard approach…