Underdetermined Source Separation Based on Generalized Multichannel Variational Autoencoder
Sign Up to like & getrecommendations! Published in 2019 at "IEEE Access"
DOI: 10.1109/access.2019.2954120
Abstract: This paper deals with a multichannel audio source separation problem under underdetermined conditions. Multichannel non-negative matrix factorization (MNMF) is a powerful method for underdetermined audio source separation, which adopts the NMF concept to model and… read more here.
Keywords: multichannel variational; method; source separation; variational autoencoder ... See more keywords
Supervised Determined Source Separation with Multichannel Variational Autoencoder
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DOI: 10.1162/neco_a_01217
Abstract: This letter proposes a multichannel source separation technique, the multichannel variational autoencoder (MVAE) method, which uses a conditional VAE (CVAE) to model and estimate the power spectrograms of the sources in a mixture. By training… read more here.
Keywords: supervised determined; variational autoencoder; multichannel variational; source ... See more keywords
Multichannel Variational Autoencoder-Based Speech Separation in Designated Speaker Order
Sign Up to like & getrecommendations! Published in 2022 at "Symmetry"
DOI: 10.3390/sym14122514
Abstract: The multichannel variational autoencoder (MVAE) integrates the rule-based update of a separation matrix and the deep generative model and proves to be a competitive speech separation method. However, the output (global) permutation ambiguity still exists… read more here.
Keywords: speaker; multichannel variational; variational autoencoder; separation ... See more keywords