Accession Number:

ADA458659

Title:

Efficient CEPSTRAL Normalization for Robust Speech Recognition

Descriptive Note:

Conference paper

Corporate Author:

CARNEGIE-MELLON UNIV PITTSBURGH PA SCHOOL OF COMPUTER SCIENCE

Report Date:

1993-01-01

Pagination or Media Count:

7.0

Abstract:

In this paper we describe and compare the performance of a series of cepstrum-based procedures that enable the CMU SPHINX-II speech recognition system to maintain a high level of recognition accuracy over a wide variety of acoustical environments. We describe the MFCDCN algorithm, an environment-independent extension of the efficient SDCN and FCDCN algorithms developed previously. We compare the performance of these algorithms with the very simple RASTA and cepstral mean normalization procedures, describing the performance of these algorithms in the context of the 1992 DARPA CSR evaluation using secondary microphones, and in the DARPA stress-test evaluation.

Subject Categories:

  • Acoustics
  • Voice Communications

Distribution Statement:

APPROVED FOR PUBLIC RELEASE