Using a Cascade of Asymmetric Resonators with Fast-Acting Compression as a Cochlear Model for Machine-Hearing Applications
Venue
Autumn Meeting of the Acoustical Society of Japan (2011), pp. 509-512
Publication Year
2011
Authors
BibTeX
Abstract
Every day, machines process many thousands of hours of audio signals through a
realistic cochlear model. They extract features, inform classifiers and
recommenders, and identify copyrighted material. The machine-hearing approach to
such tasks has taken root in recent years, because hearing-based approaches perform
better than we can do with more conventional sound-analysis approaches. We use a
bio-mimetic "cascade of asymmetric resonators with fast-acting compression"
(CAR-FAC)—an efficient sound analyzer that incorporates the hearing research
community's findings on nonlinear auditory filter models and cochlear wave
mechanics. The CAR-FAC is based on a pole–zero filter cascade (PZFC) model of
auditory filtering, in combination with a multi-time-scale coupled
automatic-gain-control (AGC) network. It uses simple nonlinear extensions of
conventional digital filter stages, and runs fast due to its low complexity. The
PZFC plus AGC network, the CAR-FAC, mimics features of auditory physiology, such as
masking, compressive traveling-wave response, and the stability of zero-crossing
times with signal level. Its output "neural activity pattern" is converted to a
"stabilized auditory image" to capture pitch, melody, and other temporal and
spectral features of the sound.
