Gaussian-Bernoulli restricted Boltzmann machines and automatic feature extraction for noise robust missing data mask estimation
Sami Keronen, Kyunghyun Cho, Tapani Raiko, Alexander A. Il'in, Kalle J. Palomäki · 2013
A missing data mask estimation method based on Gaussian-Bernoulli restricted Boltzmann machine (GRBM) trained on cross-correlation representation of the audio signal is presented in the study. The automatically learned features by the GRBM are utilized in dividing the time-frequency units of the spectrographic mask into noise and speech dominant. The system is evaluated against two baseline mask estimation methods in a reverberant multisource environment speech recognition task. The proposed system is shown to provide a performance improvement in the speech recognition accuracy over the previous multifeature approaches.