NotesFAQContact Us
Collection
Advanced
Search Tips
Peer reviewed Peer reviewed
Direct linkDirect link
ERIC Number: EJ1007559
Record Type: Journal
Publication Date: 2013
Pages: 15
Abstractor: As Provided
Reference Count: 37
ISBN: N/A
ISSN: ISSN-1560-4292
Recognizing Young Readers' Spoken Questions
Chen, Wei; Mostow, Jack; Aist, Gregory
International Journal of Artificial Intelligence in Education, v21 n4 p255-269 2013
Free-form spoken input would be the easiest and most natural way for young children to communicate to an intelligent tutoring system. However, achieving such a capability poses a challenge both to instruction design and to automatic speech recognition. To address the difficulties of accepting such input, we adopt the framework of predictable response training, which aims at simultaneously achieving linguistic predictability and educational utility. We design instruction in this framework to teach children the reading comprehension strategy of self-questioning. To filter out some misrecognized speech, we combine acoustic confidence with language modeling techniques that exploit the predictability of the elicited responses. Compared to a baseline that does neither, this approach performs significantly better in concept recall (47% vs. 28%) and precision (61% vs. 39%) on 250 unseen utterances from 34 previously unseen speakers. We conclude with some design implications for future speech enabled tutoring systems. (Contains 2 tables, 3 figures and 1 footnote.)
IOS Press. Nieuwe Hemweg 6B, Amsterdam, 1013 BG, The Netherlands. Tel: +31-20-688-3355; Fax: +31-20-687-0039; e-mail: info@iospress.nl; Web site: http://www.iospress.nl
Publication Type: Journal Articles; Reports - Research
Education Level: N/A
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: N/A