Behavioral Changes in Speakers who are Automatically Captioned in Meetings with Deaf or Hard-of-Hearing Peers

Abstract

Deaf and hard of hearing (DHH) individuals face barriers to communication in small-group meetings with hearing peers; we examine generation of captions on mobile devices by automatic speech recognition (ASR). While ASR output displays errors, we study whether such tools benefit users and influence conversational behaviors. An experiment was conducted where DHH and hearing individuals collaborated in discussions in three conditions (without an ASR-based application, with the application, and with a version indicating words for which the ASR has low confidence). An analysis of audio recordings, from each participant across conditions, revealed significant differences in speech features. When using the ASR-based automatic captioning application, hearing individuals spoke more loudly, with improved voice quality (harmonics-to-noise ratio), with a non-standard articulation (changes in F1 and F2 formants), and at a faster rate. Identifying non-standard speech in this setting has implications on the composition of data used for ASR training/testing, which should be representative of its usage context. Understanding these behavioral influences may also enable designers of ASR captioning systems to leverage these effects, to promote communication success.