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

Aalborg, Denmark
September 3-7, 2001


Noise Robust Feature Extraction for ASR Using the Aurora 2 Database

Qifeng Zhu, Markus Iseli, Xiaodong Cui, Abeer Alwan

University of California, Los Angeles, USA

Four front-end processing techniques developed for noise robust speech recognition are tested with the Aurora 2 database. These techniques include three previously published algorithms: variable frame rate analysis [Zhu and Alwan, 2000], peak isolation [Strope and Alwan, 1997], and harmonic demodulation [Zhu and Alwan, 2000], and a new technique for peak-to-valley ratio locking. Our previous work has focused on isolated digit recognition. In this paper, these algorithms are modified for recognition of connected digits. Recognition results with the Aurora 2 database show that a combination of these four techniques results in 40% error rate reduction when compared to the baseline MFCC front-end for the clean training condition, with no significant increase in computational complexity.

Full Paper

Bibliographic reference.  Zhu, Qifeng / Iseli, Markus / Cui, Xiaodong / Alwan, Abeer (2001): "Noise robust feature extraction for ASR using the Aurora 2 database", In EUROSPEECH-2001, 185-188.