Investigating the Impact of Gender Representation in ASR Training Data: a Case Study on Librispeech - Archive ouverte HAL Access content directly
Conference Papers Year :

Investigating the Impact of Gender Representation in ASR Training Data: a Case Study on Librispeech

Abstract

In this paper we question the impact of gender representation in training data on the performance of an end-to-end ASR system. We create an experiment based on the Librispeech corpus and build 3 different training corpora varying only the proportion of data produced by each gender category. We observe that if our system is overall robust to the gender balance or imbalance in training data, it is nonetheless dependant of the adequacy between the individuals present in the training and testing sets.
Fichier principal
Vignette du fichier
garnerin-etal-camera-ready.pdf (247 Ko) Télécharger le fichier
Origin : Files produced by the author(s)

Dates and versions

hal-03472117 , version 1 (09-12-2021)

Identifiers

Cite

Mahault Garnerin, Solange Rossato, Laurent Besacier. Investigating the Impact of Gender Representation in ASR Training Data: a Case Study on Librispeech. 3rd Workshop on Gender Bias in Natural Language Processing, Aug 2021, Online, France. pp.86-92, ⟨10.18653/v1/2021.gebnlp-1.10⟩. ⟨hal-03472117⟩
159 View
235 Download

Altmetric

Share

Gmail Facebook Twitter LinkedIn More