3 papers
cs.LG2018
Fast MVAE: Joint separation and classification of mixed sources based on multichannel variational autoencoder with auxiliary classifier
Li Li, Hirokazu Kameoka, Shoji Makino
This paper proposes an alternative algorithm for multichannel variational autoencoder (MVAE), a recently proposed multichannel source separation approach. While MVAE is notable in…
stat.ML2018
Generalized Multichannel Variational Autoencoder for Underdetermined Source Separation
Shogo Seki, Hirokazu Kameoka, Li Li +2
This paper deals with a multichannel audio source separation problem under underdetermined conditions. Multichannel Non-negative Matrix Factorization (MNMF) is one of powerful appr…
stat.ML2018
Semi-blind source separation with multichannel variational autoencoder
Hirokazu Kameoka, Li Li, Shota Inoue +1
This paper proposes a multichannel source separation technique called the multichannel variational autoencoder (MVAE) method, which uses a conditional VAE (CVAE) to model and estim…