EUROSPEECH 2001 Scandinavia
7th European Conference on Speech Communication and Technology

Aalborg, Denmark
September 3-7, 2001


An Auditory System-Based Feature for Robust Speech Recognition

Qi Li, Frank K. Soong, Olivier Siohan

Bell Labs, Lucent Technologies, USA

An auditory feature extraction algorithm for robust speech recognition in adverse acoustic environments is presented. The feature computation is comprised of an outer-middle-ear transfer function, FFT, frequency conversion from linear to the Bark scale, auditory filtering, nonlinearity, and discrete cosine transform. The feature is evaluated in two tasks: connected-digit recognition and large vocabulary continuous speech recognition. The tested data were under various noise conditions, including handset and hands-free speech data in landline and wireless communications with additive car and babble noise. Compared with the LPCC, MFCC, MEL-LPCC, and PLP features, the proposed feature has an average 20% to 30% string error rate reduction on the connected-digit task, and 8% to 14% word error rate reduction on the Wall Street Journal task in various additive noise conditions.

Full Paper

Bibliographic reference.  Li, Qi / Soong, Frank K. / Siohan, Olivier (2001): "An auditory system-based feature for robust speech recognition", In EUROSPEECH-2001, 619-622.