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

Autor:	Glasser, Abraham, Kushalnagar, Kesavan, Kushalnagar, Raja
Rok vydání:	2019
Předmět:	Computer Science - Human-Computer Interaction Computer Science - Sound Electrical Engineering and Systems Science - Audio and Speech Processing
Druh dokumentu:	Working Paper
DOI:	10.1145/3132525.3134819
Popis:	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. Comment: 2 pages, 3 figures
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/1909.01167 Zobrazit plný text záznamu View this record from Arxiv