Automatic speech recognition: a communication perspective

Author

Atal, Bishnu S.

Author_Institution

AT&T Labs., Florham Park, NJ, USA

Volume

1

fYear

1999

fDate

15-19 Mar 1999

Firstpage

457

Abstract

Speech recognition is usually regarded as a problem in the field of pattern recognition, where one first estimates the probability density function of each pattern to be recognized and then uses Bayes theorem to identify the pattern which provides the highest likelihood for the observed speech data. In this paper, we take a different approach to this problem. In speech recognition, the goal is communication of information by voice and we discuss the basics of speech recognition from a communication perspective. The speech signal at the acoustic level has a bit rate of 64 kb/s but the underlying sound patterns have an information rate of less than 100 b/s. What is the role of this high bit rate at the acoustic level? We discuss the principles of decoding patterns that are submerged in an ocean of seemingly irrelevant information

Keywords

acoustic signal processing; channel capacity; pattern recognition; probability; speech recognition; 64 kbit/s; Bayes theorem; acoustic level; automatic speech recognition; bit rate; channel capacity; information communication; information rate; observed speech data; probability density function; sound patterns decoding; speech signal; statistical pattern recognition; Application software; Automatic speech recognition; Bit rate; Pattern recognition; Performance analysis; Probability density function; Spectral analysis; Speech analysis; Speech recognition; Underwater acoustics;

fLanguage

English

Publisher

ieee

Conference_Titel

Acoustics, Speech, and Signal Processing, 1999. Proceedings., 1999 IEEE International Conference on

Conference_Location

Phoenix, AZ

ISSN

1520-6149

Print_ISBN

0-7803-5041-3

Type

conf

DOI

10.1109/ICASSP.1999.758161

Filename

758161