Feasibility of Using Automatic Speech Recognition with Voices of Deaf and Hard-of-Hearing Individuals

TL;DR

This paper evaluates the feasibility of using existing speech recognition technology for deaf and hard-of-hearing individuals, revealing high error rates and usability challenges in current commercial systems.

Contribution

It provides empirical evidence of the limitations of current speech recognition for DHH users and highlights the need for alternative communication methods.

Findings

Deaf speech has approximately 78% word error rate in commercial systems.

Hearing speech has about 18% word error rate.

Current speech-controlled interfaces are not suitable for DHH individuals.

Abstract

Many personal devices have transitioned from visual-controlled interfaces to speech-controlled interfaces to reduce device costs and interactive friction. This transition has been hastened by the increasing 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 deaf and hard of hearing people. Therefore, it might be wise to pursue other methods for deaf persons to deliver natural commands to computers.