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An efficient robust sound classification algorithm for hearing aids.

Peter Nordqvist1, Arne Leijon

  • 1Department of Speech, Music and Hearing, Drottning Kristinas v. 31, Royal Institute of Technology, SE-100 44 Stockholm, Sweden. nordq@speech.kth.se

The Journal of the Acoustical Society of America
|July 9, 2004
PubMed
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This study presents an efficient hidden Markov model algorithm for sound classification, enabling hearing aids to adapt to different environments. The robust system achieves high accuracy in distinguishing speech in noise, babble, and clean speech.

Area of Science:

  • Audiology
  • Signal Processing
  • Machine Learning

Background:

  • Hearing aids require advanced sound classification to adapt to diverse acoustic environments.
  • Current systems may struggle with varying signal-to-noise ratios and acoustic variations.
  • User preferences necessitate personalized hearing aid behavior adjustments.

Purpose of the Study:

  • To develop an efficient and robust sound classification algorithm for hearing aids.
  • To distinguish between three key listening environments: speech in traffic noise, speech in babble, and clean speech.
  • To ensure the algorithm is independent of signal-to-noise ratio and absolute acoustic features.

Main Methods:

  • Utilized hidden Markov models (HMMs) for sound classification.
  • Focused on modulation characteristics of the audio signal.

Related Experiment Videos

  • Ignored absolute sound pressure level and spectrum shape for robustness.

    • Main Results:

    • Achieved high classification hit rates of 96.7%-99.5% for known environment categories.
    • Demonstrated low false-alarm rates between 0.2%-1.7%.
    • The algorithm proved robust against irrelevant acoustic variations.

    Conclusions:

    • The developed algorithm is efficient, robust, and suitable for hearing aid implementation.
    • It enables automatic hearing aid adaptation to different listening environments.
    • The method offers high accuracy and low resource consumption for digital signal processing (DSP) hearing instruments.