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The potential role of speech production models in automatic speech recognition

R C Rose1, J Schroeter, M M Sondhi

  • 1AT&T Bell Laboratories, Murray Hill, New Jersey 07974-0636, USA.

The Journal of the Acoustical Society of America
|March 1, 1996
PubMed
Summary

This study explores integrating speech production models into automatic speech recognition (ASR). It focuses on articulatory representations for ASR, separate from speech perception, to improve existing systems.

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Area of Science:

  • Computational Linguistics
  • Speech Processing
  • Artificial Intelligence

Background:

  • Automatic speech recognition (ASR) systems traditionally do not leverage detailed speech production information.
  • Understanding the physical process of speech production offers potential for ASR enhancement.

Purpose of the Study:

  • To investigate the challenges and applicability of using speech production models within ASR frameworks.
  • To explore the integration of articulatory representations into current ASR systems.

Main Methods:

  • Focus on articulatory representations relevant to ASR, distinct from speech perception.
  • Integration of speech production models into established ASR formalisms.

Main Results:

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  • Identified issues associated with applying speech production models to ASR.
  • Demonstrated methods for integrating articulatory features into existing ASR architectures.
  • Conclusions:

    • Speech production models offer a viable, though challenging, avenue for improving ASR.
    • Further research into integrating articulatory information can enhance ASR performance.