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

arXiv: https://arxiv.org/abs/1909.01167 · HTML: https://mlsanity.com/paper/1909.01167/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 3 Sep 2019.

## Built on by (most cited first, 2 of 2)

- [MyMove: Facilitating Older Adults to Collect In-Situ Activity Labels on a Smartwatch with Speech](https://mlsanity.com/paper/2204.00145/) (2022)
- [Sensory-driven microinterventions for improved health and wellbeing](https://mlsanity.com/paper/2503.14102/) (2025)

## Abstract (arXiv)

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.