TY - GEN
T1 - How spoken language corpora can refine current speech motor training methodologies
AU - Umanski, Daniil
AU - Schiller, Niels O.
AU - Sangati, Federico
N1 - Publication details (e.g. title, author(s), publication statuses and dates) are captured on an “AS IS” and “AS AVAILABLE” basis at the time of record harvesting from the data source. Suggestions for further amendments or supplementary information can be sent to [email protected].
PY - 2010
Y1 - 2010
N2 - The growing availability of spoken language corpora presents new opportunities for enriching the methodologies of speech and language therapy. In this paper, we present a novel approach for constructing speech motor exercises, based on linguistic knowledge extracted from spoken language corpora. In our study with the Dutch Spoken Corpus, syllabic inventories were obtained by means of automatic syllabification of the spoken language data. Our experimental syllabification method exhibited a reliable performance, and allowed for the acquisition of syllabic tokens from the corpus. Consequently, the syllabic tokens were integrated in a tool for clinicians, a result which holds the potential of contributing to the current state of speech motor training methodologies. © 2010 Association for Computational Linguistics.
AB - The growing availability of spoken language corpora presents new opportunities for enriching the methodologies of speech and language therapy. In this paper, we present a novel approach for constructing speech motor exercises, based on linguistic knowledge extracted from spoken language corpora. In our study with the Dutch Spoken Corpus, syllabic inventories were obtained by means of automatic syllabification of the spoken language data. Our experimental syllabification method exhibited a reliable performance, and allowed for the acquisition of syllabic tokens from the corpus. Consequently, the syllabic tokens were integrated in a tool for clinicians, a result which holds the potential of contributing to the current state of speech motor training methodologies. © 2010 Association for Computational Linguistics.
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UR - https://www.scopus.com/record/pubmetrics.uri?eid=2-s2.0-84859990770&origin=recordpage
M3 - RGC 32 - Refereed conference paper (with host publication)
SN - 9781617388088
T3 - ACL 2010 - 48th Annual Meeting of the Association for Computational Linguistics, Proceedings of the Conference
SP - 37
EP - 42
BT - ACL 2010 - 48th Annual Meeting of the Association for Computational Linguistics, Proceedings of the Conference
T2 - 48th Annual Meeting of the Association for Computational Linguistics, ACL 2010
Y2 - 11 July 2010 through 16 July 2010
ER -