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Speech Reception Threshold Estimation via EEG-Based Continuous Speech Envelope Reconstruction.

Heidi B Borges1,2, Johannes Zaar1,3, Emina Alickovic1,4

  • 1Eriksholm Research Centre, Snekkersten, Denmark.

The European Journal of Neuroscience
|March 27, 2025
PubMed
Summary
This summary is machine-generated.

This study estimates speech reception threshold (SRT) using electroencephalography (EEG) and speech envelope reconstruction. Results show EEG-based SRT estimation is accurate and influenced by signal-to-noise ratio (SNR), impacting neural responses.

Keywords:
EEG measuresenvelope trackingneural decodingspeech in noisespeech intelligibility

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Area of Science:

  • Neuroscience
  • Auditory Neuroscience
  • Signal Processing

Background:

  • Accurate estimation of the speech reception threshold (SRT) is crucial for diagnosing hearing impairments.
  • Electroencephalography (EEG) offers a non-invasive method to study auditory processing.
  • Speech envelope reconstruction from EEG provides insights into neural encoding of speech.

Purpose of the Study:

  • To investigate EEG-based speech envelope reconstruction for estimating SRT (SRTneuro).
  • To examine the influence of signal-to-noise ratio (SNR) on the temporal response function (TRF) in auditory processing.
  • To correlate SNR effects on envelope reconstruction and TRF with underlying neural mechanisms.

Main Methods:

  • Recorded EEG from 20 normal-hearing participants listening to continuous speech in varying noise levels.
  • Trained a linear decoder to reconstruct speech envelope from EEG.
  • Calculated reconstruction accuracy (Pearson's correlation) and estimated SRTneuro.
  • Analyzed TRF components (latency, amplitude) across different SNRs.

Main Results:

  • SRTneuro estimates were within 3 dB of behavioral SRT for all participants.
  • Increasing SNR significantly decreased TRF component latencies (N1, P2).
  • Increasing SNR significantly increased TRF component amplitude magnitudes (N1, P2).

Conclusions:

  • EEG-based speech envelope reconstruction is a viable method for SRT estimation.
  • SNR significantly impacts both speech envelope reconstruction accuracy and TRF characteristics.
  • These findings suggest a shared neural basis for envelope encoding and TRF modulation by SNR.