7th International Conference on Spoken Language Processing

September 16-20, 2002
Denver, Colorado, USA

Robust Feature Extraction in a Variety of Input Devices on the Basis of ETSI Standard DSR Front-End

Satoru Tsuge, Shingo Kuroiwa, Masami Shishibori, Fuji Ren, Kenji Kita

Tokushima University, Japan

This paper reports an evaluation of European Telecommunications Standards Institute (ETSI) standard Distributed Speech Recognition (DSR) front-end through continuous word recognition on a Japanese speech corpus and proposes a method, the Bias Removal Method (BRM), that reduces the distortion between feature vector and VQ codebook. Experimental results show that using non-quantized features in acoustic model training procedure can improve the recognition performance of DSR front-end features and that the proposed method can improve recognition performances of DSR front-end feature.

Full Paper

Bibliographic reference.  Tsuge, Satoru / Kuroiwa, Shingo / Shishibori, Masami / Ren, Fuji / Kita, Kenji (2002): "Robust feature extraction in a variety of input devices on the basis of ETSI standard DSR front-end", In ICSLP-2002, 2221-2224.