Hey ASR System! Why Aren't You More Inclusive? Automatic Speech Recognition Systems' Bias and Proposed Bias Mitigation Techniques. A Literature Review

TL;DR

This literature review examines biases in Automatic Speech Recognition systems related to gender, race, and disabilities, and discusses various techniques for mitigating these biases to create more inclusive and accessible speech technologies.

Contribution

It provides a comprehensive survey of existing bias mitigation techniques in ASR systems and highlights future research directions for developing more equitable speech recognition technologies.

Findings

Biases against gender, race, and disabilities are prevalent in current ASR systems.

Various debiasing techniques show promise but have limitations.

Future research opportunities include developing more inclusive and accessible ASR models.

Abstract

Speech is the fundamental means of communication between humans. The advent of AI and sophisticated speech technologies have led to the rapid proliferation of human-to-computer-based interactions, fueled primarily by Automatic Speech Recognition (ASR) systems. ASR systems normally take human speech in the form of audio and convert it into words, but for some users, it cannot decode the speech, and any output text is filled with errors that are incomprehensible to the human reader. These systems do not work equally for everyone and actually hinder the productivity of some users. In this paper, we present research that addresses ASR biases against gender, race, and the sick and disabled, while exploring studies that propose ASR debiasing techniques for mitigating these discriminations. We also discuss techniques for designing a more accessible and inclusive ASR technology. For each approach surveyed, we also provide a summary of the investigation and methods applied, the ASR systems and corpora used, and the research findings, and highlight their strengths and/or weaknesses. Finally, we propose future opportunities for Natural Language Processing researchers to explore in the next level creation of ASR technologies.