Minority English Dialects Vulnerable to Automatic Speech Recognition Inaccuracy

The Automatic Speech Recognition (ASR) models that power voice assistants like Amazon Alexa may have difficulty transcribing English speakers with minority dialects.

A study by Georgia Tech and Stanford researchers compared the transcribing performance of leading ASR models for people using Standard American English (SAE) and three minority dialects — African American Vernacular English (AAVE), Spanglish, and Chicano English.

Interactive Computing Ph.D. student Camille Harris is the lead author of a paper accepted into the 2024 Conference on Empirical Methods in Natural Language Processing (EMNLP) this week in Miami.