Sixth International Conference on Spoken Language Processing
October 16-20, 2000
Auditory Spectrum Based Features (ASBF) for Robust Speech Recognition
Chi H. Yim, Oscar C. Au, Wanggen Wan, Cyan L. Keung, Carrson C. Fung
Human Language Technology Center,
Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong
MFCC are features commonly used in speech recognition
systems today. The recognition accuracy of systems
using MFCC is known to be high in clean speech
environment, but it drops greatly in noisy environment.
In this paper, we propose new features called the auditory
spectrum based features (ASBF) that are based on the
cochlear model of the human auditory system. These new
features can track the formants and the selection scheme
of these features is based on the second order difference
cochlear model and the primary auditory nerve
processing model. In our experiment, the performance of
MFCC and the ASBF are compared in clean and noisy
environments. The results suggest that the ASBF are
much more robust to noise than MFCC.
Yim, Chi H. / Au, Oscar C. / Wan, Wanggen / Keung, Cyan L. / Fung, Carrson C. (2000):
"Auditory spectrum based features (ASBF) for robust speech recognition",
In ICSLP-2000, vol.2, 979-982.