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Related Experiment Videos

Detecting stop consonants in continuous speech.

P Niyogi1, M M Sondhi

  • 1Bell Laboratories, Lucent Technologies, Murray Hill, New Jersey 07974, USA. niyogi@cs.uchicago.edu

The Journal of the Acoustical Society of America
|February 28, 2002
PubMed
Summary
This summary is machine-generated.

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This study explores creating an optimal filter for detecting stop consonants in continuous speech. The research evaluates filter performance for both human and machine speech recognition systems.

Area of Science:

  • Speech Processing
  • Acoustic Phonetics
  • Machine Learning

Background:

  • Detecting stop consonants in continuous speech presents significant challenges.
  • Accurate stop consonant identification is crucial for speech recognition.

Purpose of the Study:

  • To develop and evaluate an optimal filter for identifying stop consonants.
  • To explore linear and nonlinear filter approaches for speech detection.

Main Methods:

  • Formulating the problem as finding an optimal filter.
  • Designing and testing variants of a canonical stop detector.
  • Analyzing filter performance on speech representations.

Main Results:

  • Several variants of a canonical stop detector were evaluated.

Related Experiment Videos

  • The study discusses the performance of different filter types.

    • Conclusions:

    • The findings have implications for improving both human and machine speech recognition.
    • Optimal filter design is key to accurate stop consonant detection.