DocumentCode
3749233
Title
Speech disabilities in adults and the suitable speech recognition software tools - a review
Author
Balaji V;G. Sadashivappa
Author_Institution
Department of Computer Science, Christ University, Bangalore, India
fYear
2015
Firstpage
559
Lastpage
564
Abstract
Speech impairment, though not a major obstacle, is still a problem for people who suffer from it, while they are making public presentations. This paper describes the different speech disabilities in adults and reviews the available software and other computer based tools that facilitate better communication for people with speech impairment. The motivation for this writing has been the fact that stuttering, one of the types of speech disability has affected about 1 percentage of the people worldwide. This fact was provided by the Stuttering Foundation of America, a Non-profit Organization, functioning since 1947. A solution to stuttering is expected to benefit a considerable population. Speech recognition software tools help people with disabilities use their computers and other hand held devices to satisfy their day-to-day needs which otherwise, require dedicated domestic help and also question the person´s ability to be independent. ASR (Automatic Speech Recognition) systems are popular among the common people and people with motor disabilities, while using these techniques for the treatment of speech correction is a current research field and is of interest to SLPs/SLTs (Speech Language Pathologist / Speech Language Therapist). On-going research also includes development of ASR based software to facilitate comfortable oral communication with people suffering from speech dysfunctions, i.e., in the domain of AAC (Augmentative and Alternative Communication).
Keywords
"Speech","Speech recognition","Hidden Markov models","Speech processing","Mathematical model","Computers","Training"
Publisher
ieee
Conference_Titel
Computing and Network Communications (CoCoNet), 2015 International Conference on
Type
conf
DOI
10.1109/CoCoNet.2015.7411243
Filename
7411243
Link To Document