Signal Processing for Robust Speech Recognition

Abstract

This paper describes a series of cepstral-based compensation procedures that render the SPHINX-II system more robust with respect to acoustical environment. The first algorithm. phone-dependent cepstral compensation, is similar in concept to the previously-described MFCDCN method, except that cepstral compensation vectors are selected according to the current phonetic hypothesis, rather than on the basis of SNR or VQ codeword identity. We also describe two procedures to accomplish adaptation of the VQ codebook for new environments, as well as the use of reduced-bandwidth frequency analysis to process telephone-band-width speech. Use of the various compensation algorithms in consort produces a reduction of error rates for SPHINX-II by as much as 40 percent relative to the rate achieved with cepstral mean normalization alone, in both development test sets and in the context of the 1993 ARPA CSR evaluations.

Open PDF

Document Details

Document Type
Technical Report
Publication Date
Jan 01, 1994
Accession Number
ADA457798

Entities

People

  • Alejandro Acero
  • Fu-hua Liu
  • Pedro J. Moreno
  • Richard M. Stern

Organizations

  • Carnegie Mellon University

Tags

Communities of Interest

  • C4I

DTIC Thesaurus Topics

  • Abstracts
  • Accuracy
  • Algorithms
  • Automated Speech Recognition
  • Bandwidth
  • Compensation
  • Computer Science
  • Databases
  • Environment
  • Frequency
  • Information Science
  • Probability
  • Probability Density Functions
  • Signal Processing
  • Standards
  • Test And Evaluation
  • Test Sets

Readers

  • Speech Processing/Speech Recognition.
  • Systems Analysis and Design

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference