Exploring Gender Disparities in Automatic Speech Recognition Technology

Hend ElGhazaly, Bahman Mirheidari, Nafise Sadat Moosavi, Heidi Christensen
2/25/2025
cs.CLcs.SDeess.AS

No confident code implementation found for this paper. 2 possible matches can be shown below.

Abstract

This study investigates factors influencing Automatic Speech Recognition (ASR) systems' fairness and performance across genders, beyond the conventional examination of demographics. Using the LibriSpeech dataset and the Whisper small model, we analyze how performance varies across different gender representations in training data. Our findings suggest a complex interplay between the gender ratio in training data and ASR performance. Optimal fairness occurs at specific gender distributions rather than a simple 50-50 split. Furthermore, our findings suggest that factors like pitch variability can significantly affect ASR accuracy. This research contributes to a deeper understanding of biases in ASR systems, highlighting the importance of carefully curated training data in mitigating gender bias.

View on arXivView PDF

Code Implementations

No confident code match yet

We couldn't find an author-owned or strongly-evidenced community implementation for this paper. 2 weaker matches are hidden by default — verify before relying on them.

No code implementations found yet.

Know of an implementation? Let us know in the comments below!

Similar Papers

Twists, Humps, and Pebbles: Multilingual Speech Recognition Models Exhibit Gender Performance Gaps

89% match1 repo72024

Everyone deserves their voice to be heard: Analyzing Predictive Gender Bias in ASR Models Applied to Dutch Speech Data

88% match2024

ASR-FAIRBENCH: Measuring and Benchmarking Equity Across Speech Recognition Systems

84% match2025

Acoustic-based Gender Differentiation in Speech-aware Language Models

84% match2025

DENOASR: Debiasing ASRs through Selective Denoising

84% match2024

Who Gets the Mic? Investigating Gender Bias in the Speaker Assignment of a Speech-LLM

84% match1 repo2025

Cite this paper

@article{elghazaly2025exploring,
  title  = {Exploring Gender Disparities in Automatic Speech Recognition Technology},
  author = {Hend ElGhazaly and Bahman Mirheidari and Nafise Sadat Moosavi and Heidi Christensen},
  year   = {2025},
  eprint = {2502.18434},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2502.18434v1}
}

Add a badge to your README

Shows whether official code is linked for this paper.

Code of Paper badge
[![Code of Paper](https://codeofpaper.com/badge/2502.18434.svg)](https://codeofpaper.com/paper/2502.18434)

Discussion