Name
Abstract | ||
|---|---|---|
Individuals with neuromotor speech disorders due to conditions such as Multiple Sclerosis, Parkinson Disease and Cerebral Palsy have soft and slurred speech. These individuals receive speech training to increase vocal loudness and to speak slowly and clearly. Although successful in clinical settings, generalizability of these techniques to daily conversation requires technological innovation. To address this issue we designed SpeechOmeter, a Google Glass application that provides unobtrusive real-time visual feedback on vocal loudness relative to the ambient noise level. The system also provides clinicians with treatment adherence and performance statistics in order to further personalize speech training regimes. In a longitudinal usability study 12 individuals with MS increased vocal loudness when provided with feedback. A live demonstration of SpeechOmeter will enable attendees to experience the system. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1145/2661334.2661339 | ASSETS |
Keywords | Field | DocType |
speech clarity,speech prosthesis,assistive technologies for persons with disabilities,visual feedback,screen design,assistive communication,speech therapy | Vocal loudness,Generalizability theory,Speech training,Conversation,Speech clarity,Computer science,Usability,Cerebral palsy,Speech recognition,Human–computer interaction,Slurred speech,Audiology | Conference |
Citations | PageRank | References |
1 | 0.38 | 0 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Mansoor Pervaiz | 1 | 1 | 0.38 |
| Rupal Patel | 2 | 45 | 7.47 |