HCSep 3, 2019

Deaf, Hard of Hearing, and Hearing Perspectives on using Automatic Speech Recognition in Conversation

arXiv:1909.01176v139 citations
Originality Synthesis-oriented
AI Analysis

This highlights a critical accessibility issue for DHH individuals, showing that current technology is not usable for them, which is an incremental but important finding.

The study tackled the problem of speech-controlled interfaces being inaccessible to deaf or hard of hearing (DHH) people, finding that deaf speech has a 78% word error rate compared to 18% for hearing speech in commercial systems.

Many personal devices have transitioned from visual-controlled interfaces to speech-controlled interfaces to reduce costs and interactive friction, supported by the rapid growth in capabilities of speech-controlled interfaces, e.g., Amazon Echo or Apple's Siri. A consequence is that people who are deaf or hard of hearing (DHH) may be unable to use these speech-controlled devices. We show that deaf speech has a high error rate compared to hearing speech, in commercial speech-controlled interfaces. Deaf speech had approximately a 78% word error rate (WER) compared to a hearing speech 18% WER. Our findings show that current speech-controlled interfaces are not usable by DHH people. Based on our findings, significant advances in speech recognition software or alternative approaches will be needed for deaf use of speech-controlled interfaces. We show that current speech-controlled interfaces are not usable by DHH people.

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