TY - GEN
T1 - ISCAN
T2 - 14th International ACM SIGACCESS Conference on Computers and Accessibility
AU - Trinh, Ha
AU - Waller, Annalu
AU - Vertanen, Keith
AU - Kristensson, Per Ola
AU - Hanson, Vicki L.
PY - 2012
Y1 - 2012
N2 - The high incidence of literacy deficits among people with severe speech impairments SSIhas been well documented. Without literacy skills, people with SSI are unable to effectively use orthographic-based communication systems to generate novel linguistic items in spontaneous conversation. To address this problem, phoneme-based communication systems have been proposed which enable users to create spoken output from phoneme sequences. In this paper, we investigate whether prediction techniques can be employed to improve the usability of such systems. We have developed iSCAN, a phoneme-based predictive communication system, which offers phoneme prediction and phoneme-based word prediction. A pilot study with 16 able-bodied participants showed that our predictive methods led to a 108.4% increase in phoneme entry speed and a 79.0% reduction in phoneme error rate. The benefits of the predictive methods were also demonstrated in a case study with a cerebral palsied participant. Moreover, results of a comparative evaluation conducted with the same participant after 16 sessions using iSCAN indicated that our system outperformed an orthographic-based predictive communication device that the participant has used for over 4 years.
AB - The high incidence of literacy deficits among people with severe speech impairments SSIhas been well documented. Without literacy skills, people with SSI are unable to effectively use orthographic-based communication systems to generate novel linguistic items in spontaneous conversation. To address this problem, phoneme-based communication systems have been proposed which enable users to create spoken output from phoneme sequences. In this paper, we investigate whether prediction techniques can be employed to improve the usability of such systems. We have developed iSCAN, a phoneme-based predictive communication system, which offers phoneme prediction and phoneme-based word prediction. A pilot study with 16 able-bodied participants showed that our predictive methods led to a 108.4% increase in phoneme entry speed and a 79.0% reduction in phoneme error rate. The benefits of the predictive methods were also demonstrated in a case study with a cerebral palsied participant. Moreover, results of a comparative evaluation conducted with the same participant after 16 sessions using iSCAN indicated that our system outperformed an orthographic-based predictive communication device that the participant has used for over 4 years.
UR - http://www.scopus.com/inward/record.url?scp=84869760053&partnerID=8YFLogxK
U2 - 10.1145/2384916.2384927
DO - 10.1145/2384916.2384927
M3 - Conference contribution
AN - SCOPUS:84869760053
SN - 9781450313216
SP - 57
EP - 64
BT - ASSETS'12
PB - Association for Computing Machinery
CY - New York
Y2 - 22 October 2012 through 24 October 2012
ER -