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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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Speech intelligibility prediction based on modulation frequency-selective processing.

Helia Relaño-Iborra1, Torsten Dau2

  • 1Hearing Systems Section, Department of Health Technology, Technical University of Denmark, Kgs. Lyngby 2800, Denmark; Cognitive Systems Section, Department of Applied Mathematics and Computer Science, Technical University of Denmark, Kgs, Lyngby 2800, Denmark.

Hearing Research
|September 26, 2022
PubMed
Summary
This summary is machine-generated.

Speech intelligibility models using modulation filterbanks offer insights into auditory perception. This review discusses models like sEPSM and sCASP, highlighting their strengths and weaknesses for predicting speech understanding.

Keywords:
Auditory modelingHearing impairmentModulation processingSpeech intelligibility

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Area of Science:

  • Auditory Neuroscience
  • Speech Communication
  • Signal Processing

Background:

  • Speech intelligibility models are crucial for understanding human speech perception.
  • Amplitude modulation analysis is a key component in successful speech intelligibility models.
  • Modulation filterbanks are increasingly integrated into these models.

Purpose of the Study:

  • To review speech intelligibility models incorporating modulation filterbanks.
  • To discuss the speech-based envelope power spectrum model (sEPSM) and its variants.
  • To examine the speech-based computational auditory signal processing and perception model (sCASP).

Main Methods:

  • Analysis of amplitude modulations in speech and interfering signals.
  • Review of models featuring modulation filterbank processing stages.
  • Comparison of different modeling approaches for predicting speech intelligibility.

Main Results:

  • Discussion of key processing stages in sEPSM and sCASP for various acoustic conditions.
  • Evaluation of the strengths and weaknesses of modulation-based analysis.
  • Identification of challenges in predicting hearing loss effects on speech intelligibility.

Conclusions:

  • Modulation-based models provide valuable insights into speech perception.
  • Further research is needed to refine models for predicting the impact of hearing loss.
  • These models are essential for understanding and improving communication in complex acoustic environments.