On the distribution of Mel-filtered log-spectrum of speech in additive noise
We characterize the distributions of MFLS of clean and noisy speech signals with a non-parametric approach. The joint distributions of MFLS of clean and noisy speech signals have two lobes (1st: silent/noise, 2nd: speech). We model each MFLS component by a 2-state Markov process with time-varying parameters. The enhanced MFLS (Mel-filtered log-spectrum) features are extracted using the MMSE estimates. A new front-end is proposed for robust speech recognition by separating the non-speech and speech components.
mel-filtered log-spectrum speech signal joint distribution robust speech recognition two-state gaussian markov model minimum mean square error estimation