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Foreign Accent and Forensic Speaker Identification in Voice Lineups: The Influence of Acoustic Features Based on Prosody
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A Dual-Microphone Speech Enhancement Algorithm Based on the Coherence Function.

Nima Yousefian1, Philipos C Loizou

  • 1Department of Electrical Engineering, University of Texas at Dallas, Richardson, TX 75083 USA.

IEEE Transactions on Audio, Speech, and Language Processing
|December 31, 2011
PubMed
Summary
This summary is machine-generated.

This study introduces a new dual-microphone speech enhancement method using signal coherence for noise reduction. The technique significantly improves speech intelligibility and quality, especially in noisy environments with multiple sound sources.

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Area of Science:

  • Acoustics
  • Signal Processing
  • Hearing Science

Background:

  • Speech enhancement is crucial for assistive listening devices.
  • Existing methods often struggle with multiple noise sources or require complex noise statistics.
  • Dual-microphone systems offer potential for improved noise reduction.

Purpose of the Study:

  • To propose a novel dual-microphone speech enhancement technique.
  • To evaluate the algorithm's performance in terms of speech intelligibility and quality.
  • To compare the proposed method against a conventional beamforming algorithm.

Main Methods:

  • A coherence-based criterion for noise reduction using two closely-spaced microphones.
  • Implementation without requiring noise statistics estimation.
  • Evaluation using intelligibility listening tests with normal hearing listeners.

Main Results:

  • The proposed algorithm demonstrated significant gains in speech intelligibility compared to a baseline front-microphone approach.
  • Substantially higher intelligibility was achieved over a beamforming algorithm, particularly with multiple noise sources.
  • Objective quality evaluations showed significant improvements over the beamforming method.

Conclusions:

  • The coherence-based dual-microphone speech enhancement technique offers superior performance.
  • The algorithm is effective in single and multiple-noise source scenarios.
  • It is a promising candidate for hearing aid and cochlear implant applications due to improved intelligibility and quality.