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Related Experiment Video

Updated: Nov 21, 2025

Asthma Detection Research Based on Voice Signal Processing and Machine Learning
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Microphone and Audio Compression Effects on Acoustic Voice Analysis: A Pilot Study.

Julio Cesar Cavalcanti1, Marina Englert2, Miguel Oliveira3

  • 1Universidade Estadual de Campinas (UNICAMP), Institute of Language Studies, Campinas - SP, Brazil.

Journal of Voice : Official Journal of the Voice Foundation
|January 16, 2021
PubMed
Summary

Microphone choice and audio compression significantly impact voice and speech analysis. While some acoustic parameters like fundamental frequency (f0) are robust, others like Harmonic-to-Noise Ratio (HNR) are sensitive to these variables.

Keywords:
PhoneticsSmartphoneSpeechVoice

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Area of Science:

  • Speech and Audio Processing
  • Acoustic Phonetics
  • Signal Analysis

Background:

  • Accurate voice and speech parameter acquisition is crucial for various applications.
  • The influence of recording equipment and data compression on acoustic measures is not fully understood.

Purpose of the Study:

  • To investigate the effects of different microphones and audio compression levels on key voice and speech parameters.
  • To identify acoustic measures that are robust or sensitive to variations in microphone quality and compression rates.

Main Methods:

  • Acoustic measures were recorded using a reference microphone and three test microphones with varying specifications.
  • Audio files were compressed into MP3 format at 128, 64, and 32 kbps.
  • Eight speakers produced sustained vowels ([a] and [ɛ]) captured simultaneously by all microphones and analyzed using Praat software.

Main Results:

  • Fundamental frequency (f0), second formant (F2), and jitter% were found to be relatively resistant to microphone and compression variations.
  • Harmonic-to-Noise Ratio (HNR), H1-H2, and Coefficient of Voice Production (CPP) were significantly affected by both factors.
  • Shimmer% was sensitive to audio compression, and higher compression rates led to more acoustic distortions.

Conclusions:

  • Microphone selection and audio compression critically influence the reliability of acoustic analysis.
  • Researchers and clinicians should carefully consider these factors to ensure accurate voice and speech parameter acquisition.