Feasibility of Using Automatic Speech Recognition with Voices of Deaf and Hard-of-Hearing Individuals
This highlights a critical accessibility issue for DHH individuals in using modern speech-controlled devices, but it is incremental as it primarily documents an existing problem without proposing a new solution.
The study tackled the problem of speech-controlled interfaces being inaccessible to deaf and hard-of-hearing (DHH) individuals by measuring error rates, finding that deaf speech had a 78% word error rate compared to 18% for hearing speech, indicating current systems are not usable for DHH people.
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.