33 citations · 44 across the 4 of their papers we have counts for
4 papers
FastMVAE2: On improving and accelerating the fast variational autoencoder-based source separation algorithm for determined mixtures
Li Li, Hirokazu Kameoka, Shoji Makino
This paper proposes a new source model and training scheme to improve the accuracy and speed of the multichannel variational autoencoder (MVAE) method. The MVAE method is a recentl…
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…
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…
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…