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Related Experiment Video

Updated: Oct 26, 2025

Systematic Hearing Performance Evaluation Process for Adolescents with Cochlear Implantation at Early Ages

Systematic Hearing Performance Evaluation Process for Adolescents with Cochlear Implantation at Early Ages

Published on: March 24, 2023

Quantifying Cochlear Implant Users' Ability for Speaker Identification using CI Auditory Stimuli.

Nursadul Mamun¹, Ria Ghosh¹, John H L Hansen¹

¹CRSS: Center for Robust Speech Systems; Cochlear Implant Processing Laboratory (CILab) Department of Electrical and Computer Engineering, University of Texas at Dallas, USA.

|July 26, 2021

Summary

This summary is machine-generated.

Cochlear implant (CI) users can identify a limited number of speakers using electric auditory stimuli. Performance decreases with more speakers and in noisy conditions, highlighting areas for improved CI signal processing.

Keywords:

ACE processing Cochlear-Implants Electrodograms GMM-UBM I-vectors PLDA Speaker Identification

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Area of Science:

Biomedical Engineering
Speech Processing
Auditory Neuroscience

Background:

Speaker identification (SID) is challenging in noisy environments, particularly for individuals with cochlear implants (CI).
CI users process speech via limited electric stimulation, potentially losing crucial speaker-dependent cues like pitch and formants.

Purpose of the Study:

To analyze and quantify the speaker identification capabilities of CI users based on direct electric auditory stimuli.
To investigate the impact of the number of speakers and background noise on CI user SID performance.

Main Methods:

Speech signals were processed using the CI Advanced Combined Encoder (ACE) strategy to create auditory electrodograms.
Two classifiers were trained with 50 speakers from three databases and tested under quiet and noisy conditions.

Main Results:

CI users demonstrated effective identification of a limited set of speakers.
Speaker identification accuracy significantly decreased as the number of speakers increased and in the presence of noise.

Conclusions:

CI users' ability to perform speaker identification is constrained by the number of speakers and environmental noise.
Findings suggest potential for enhancing CI signal processing strategies to improve speaker recognition for CI users.