Enhancement of noisy speech for noise robust front-end and speech reconstruction at back-end of DSR system

This paper presents a speech enhancement method for noise robust front-end and speech reconstruction at the back-end of Distributed Speech Recognition (DSR). The speech noise removal algorithm is based on a two stage noise filtering LSAHT by log spectral amplitude speech estimator (LSA) and harmonic tunneling (HT) prior to feature extraction. The noise reduced features are transmitted with some parameters, viz., pitch period, the number of harmonic peaks from the mobile terminal to the server along noise-robust mel-frequency cepstral coefficients. Speech reconstruction at the back end is achieved by sinusoidal speech representation. Finally, the performance of the system is measured by the segmental signal-noise ratio, MOS tests, and the recognition accuracy of an Automatic Speech Recognition (ASR) in comparison to other noise reduction methods.