A survey of artificial intelligence approaches in blind source separation
In various signal processing applications, such as audio signal recovery, the extraction of
desired signals from a mixture of other signals is a crucial task. To achieve superior …
desired signals from a mixture of other signals is a crucial task. To achieve superior …
Complex angular central Gaussian mixture model for directional statistics in mask-based microphone array signal processing
Microphone array signal processing based on time-frequency masks has been applied
successfully to various tasks including source separation, denoising, source localization …
successfully to various tasks including source separation, denoising, source localization …
Integration of neural networks and probabilistic spatial models for acoustic blind source separation
L Drude, R Haeb-Umbach - IEEE Journal of Selected Topics in …, 2019 - ieeexplore.ieee.org
We formulate a generic framework for blind source separation (BSS), which allows
integrating data-driven spectro-temporal methods, such as deep clustering and deep …
integrating data-driven spectro-temporal methods, such as deep clustering and deep …
[HTML][HTML] A novel Bayesian blind source separation approach for extracting non-stationary and discontinuous components from structural health monitoring data
We propose a new method to explore the blind source separation (BSS) of heterogeneous
structural health monitoring (SHM) data containing non-stationary and temporally …
structural health monitoring (SHM) data containing non-stationary and temporally …
Informed spatial filtering for sound extraction using distributed microphone arrays
M Taseska, EAP Habets - IEEE/ACM transactions on audio …, 2014 - ieeexplore.ieee.org
Hands-free acquisition of speech is required in many human-machine interfaces and
communication systems. The signals received by integrated microphones contain a desired …
communication systems. The signals received by integrated microphones contain a desired …
Bayesian nonparametrics for microphone array processing
Sound source localization and separation from a mixture of sounds are essential functions
for computational auditory scene analysis. The main challenges are designing a unified …
for computational auditory scene analysis. The main challenges are designing a unified …
Probabilistic spatial dictionary based online adaptive beamforming for meeting recognition in noisy and reverberant environments
Here we propose online adaptive beamforming for automatic speech recognition (ASR) in
meetings in noisy, reverberant environments. The proposed method is based on recently …
meetings in noisy, reverberant environments. The proposed method is based on recently …
Variational inference for Watson mixture model
J Taghia, A Leijon - IEEE Transactions on Pattern Analysis and …, 2015 - ieeexplore.ieee.org
This paper addresses modelling data using the Watson distribution. The Watson distribution
is one of the simplest distributions for analyzing axially symmetric data. This distribution has …
is one of the simplest distributions for analyzing axially symmetric data. This distribution has …
Source counting in speech mixtures by nonparametric Bayesian estimation of an infinite Gaussian mixture model
In this paper we present a source counting algorithm to determine the number of speakers in
a speech mixture. In our proposed method, we model the histogram of estimated directions …
a speech mixture. In our proposed method, we model the histogram of estimated directions …
Parameter-adaptive variational autoencoder for linear/nonlinear blind source separation
Blind source separation (BSS) serves as an important technique in the field of structural
health monitoring (SHM), particularly for solving modal decomposition tasks. This study …
health monitoring (SHM), particularly for solving modal decomposition tasks. This study …