Sixth International Conference on Spoken Language Processing
October 16-20, 2000
A High-Performance Auditory Feature for Robust Speech Recognition
Qi Li, Frank K. Soong, Olivier Siohan
Bell Labs, Lucent Technologies, Murray Hill, NJ, USA
An auditory feature extraction algorithm for robust speech
recognition in adverse acoustic environments is proposed.
Based on the analysis of human auditory system, the feature
extraction algorithm consists of several modules: FFT,
outer-middle-ear transfer function, frequency conversion from
linear to Bark scales, auditory filtering, nonlinearity, and discrete
cosine transform. Three recognition experiments have
been conducted on connected digit recognition in wireless
and land-line communications using handsets and handsfree
microphones. Compared to LPCC and MFCC features,
the proposed feature has shown 11% to 23% error-rate reductions
on average in handset and hands-free acoustic environments
in the experiments.
Li, Qi / Soong, Frank K. / Siohan, Olivier (2000):
"A high-performance auditory feature for robust speech recognition",
In ICSLP-2000, vol.3, 51-54.