Incorporating formant cues into distributed speech recognition systems

The current front-end for distributed speech recognition (DSR) systems provided by European Telecommunications Standards Institute (ETSI) is mainly based on the state-of-the- art MFCC features. The method proposed in this paper aims to improve the performance of the present ETSI DSR-XAFE (XAFE: extended Audio Front-End). For this purpose two sets of acoustical features namely formant-like features and MFCC features are integrated under the multi-stream framework to form a feature vector which is more robust against additive noise. It is shown that for noisy speech, combining cepstral coefficients with main spectral peaks also known as formant-like features, using the multi-stream framework, leads to significant improvement in word recognition accuracy relative to word accuracy obtained for MFCCs alone.