Research in Continuous Speech Recognition.

Abstract

This annual report describes the work performed during the past year in an ongoing effort to design and implement a system that performs phonetic recognition of continuous speech. The general approach used it to develop a Hidden Markov Model (HMM) of speech parameter movements, which can be used to distinguish among the different phonemes. The resulting phoneme models incorporate the contextural effects of neighboring phonemes. One main aspect of this research is to incorporate both spectral parameters and acoustic-phonetic features into the HMM formalism. (Author)

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Document Details

Document Type
Technical Report
Publication Date
Dec 01, 1983
Accession Number
ADA136990

Entities

People

  • J. Makhoul
  • R. M. Schwartz
  • Y. L. Chow

Organizations

  • BBN Technologies

Tags

Communities of Interest

  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Algorithms
  • Automated Speech Recognition
  • Computations
  • Computer Programming
  • Databases
  • Debugging
  • Decoding
  • Dynamic Programming
  • Estimators
  • Hidden Markov Models
  • Markov Chains
  • Markov Models
  • Operating Systems
  • Pattern Recognition
  • Probabilistic Models
  • Probability
  • Signal Processing

Readers

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

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference