A posteriori SNR weighted energy based variable frame rate analysis for speech recognition

Abstract

Abstract This paper presents a variable frame rate (VFR) analysis method that uses an a posteriori signal-to-noise ratio (SNR) weighted energy distance for frame selection. The novelty of the method consists in the use of energy distance (instead of cepstral distance) to make it computationally efficient and the use of SNR weighting to emphasize the reliable regions in speech signals. The VFR method is applied to speech recognition in two scenarios. First, it is used for improving speech recognition performance in noisy environments. Secondly, the method is used for source coding in distributed speech recognition where the target bit rate is met by adjusting the frame rate, yielding a scalable coding scheme. Prior to recognition in the server, frames are repeated so that the original frame rate is restored. Very encouraging results are obtained for both noise robustness and source coding. Index Terms : speech recognition, speech analysis, variable frame rate, noise robustness, source coding