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Related Experiment Video

Updated: Jun 5, 2026

Memorization-Based Training and Testing Paradigm for Robust Vocal Identity Recognition in Expressive Speech Using Event-Related Potentials Analysis

Memorization-Based Training and Testing Paradigm for Robust Vocal Identity Recognition in Expressive Speech Using Event-Related Potentials Analysis

Published on: August 9, 2024

Predicting the intelligibility of vocoded speech.

Fei Chen¹, Philipos C Loizou

¹Department of Electrical Engineering, University of Texas at Dallas, Richardson, Texas 75080-3021, USA.

Ear and Hearing

|January 6, 2011

Summary

Coherence-based and Speech Transmission Index (STI)-based measures effectively predict vocoded speech intelligibility. These indices are crucial for developing advanced cochlear implant speech coding algorithms.

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Published on: September 27, 2024

Area of Science:

Auditory Perception
Speech Processing
Signal Analysis

Background:

Vocoder simulations are vital for understanding speech processing in cochlear implants.
Assessing speech intelligibility in noisy and distorted conditions is challenging.
Existing intelligibility measures may not fully capture the nuances of vocoded speech.

Purpose of the Study:

To evaluate the predictive performance of various speech intelligibility indices for vocoded speech.
To determine which measures best correlate with human intelligibility scores in vocoded speech conditions.

Main Methods:

Vocoded speech stimuli were created under 80 conditions varying in signal-to-noise ratio and masker type.
Normal-hearing listeners identified vocoded sentences, providing intelligibility scores.
Correlations between intelligibility scores and multiple speech intelligibility measures (e.g., STI, coherence-based) were analyzed.

Main Results:

Coherence-based and Speech Transmission Index (STI)-based measures demonstrated the highest correlations with intelligibility (r=0.9-0.96).
STI-based measures achieved high correlation (r=0.92) when using high modulation rates (100 Hz).
Coherence-based measures showed slightly higher correlations for tone-vocoded speech compared to electric-acoustic stimulation (EAS) vocoded speech.

Conclusions:

Speech intelligibility indices, particularly coherence-based and STI-based measures, can effectively predict vocoded speech intelligibility.
A derived coherence measure emphasizing spectral transitions showed the highest correlation (r=0.96).
High modulation rates (100 Hz) are essential for STI-based measures to accurately model vocoded speech intelligibility, especially with limited spectral information.