Sixth International Conference on Spoken Language Processing
October 16-20, 2000
Hidden Markov Model Environmental Compensation for Automatic Speech Recognition on Hand-Held Mobile Devices
Bojana Gajic (1), Richard C. Rose (2)
(1) Norwegian University of Science and Technology (NTNU), Trondheim, Norway
This paper is concerned with applying hidden Markov model compensation
techniques for improving the performance of automatic
speech recognition (ASR) based services on hand-held mobile devices.
The implementation and evaluation of an ASR based task
for a mobile, hand-held device is presented, along with a set of
compensation techniques that are used to compensate speaker independent
hidden Markov models with respect to environmental
and transducer variability. A technique for combined environment/
transducer compensation is shown to significantly reduce
the effects of environmental mismatch. The overall performance
degradation with respect to clean conditions was reduced from
41.7 percent to 10.4 percent for speech spoken through a far–field
microphone in an office environment, and from 79.2 percent to
39.8 percent for the same transducer in a noisy cafeteria envionment.
(2) AT&T Labs-Research, Florham Park, NJ, USA
Gajic, Bojana / Rose, Richard C. (2000):
"Hidden Markov model environmental compensation for automatic speech recognition on hand-held mobile devices",
In ICSLP-2000, vol.1, 405-408.