Combining multi-band and frequency-filtering techniques for speech recognition in noisy environments

Research output: Chapter in Book/Report/Conference proceedingChapter (peer-reviewed)peer-review


While current speech recognisers give acceptable performance in carefully controlled environments, their performance degrades rapidly when they are applied in more realistic situations. Generally, the environmental noise may be classified into two classes: the wide-band noise and narrow band noise. While the multi-band model has been shown to be capable of dealing with speech corrupted by narrow-band noise, it is ineffective for wide-band noise. In this paper, we suggest a combination of the frequency-filtering technique with the probabilistic union model in the multi-band approach. The new system has been tested on the TIDIGITS database, corrupted by white noise, noise collected from a railway station, and narrow-band noise, respectively. The results have shown that this approach is capable of dealing with noise of narrow-band or wide-band characteristics, assuming no knowledge about the noisy environment.
Original languageEnglish
Title of host publicationText, Speech and Dialogue
Number of pages6
ISBN (Electronic)978-3-540-45323-9
Publication statusPublished - 2000

Publication series

NameLecture Notes in Computer Science
ISSN (Electronic)0302-9743


Dive into the research topics of 'Combining multi-band and frequency-filtering techniques for speech recognition in noisy environments'. Together they form a unique fingerprint.

Cite this