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Fast algorithms for phone classification and recognition using segment-based models

Digalakis Vasilis, Ostendorf M., Rohlicek J. R.

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URIhttp://purl.tuc.gr/dl/dias/E2EA7355-151C-41CB-BE98-13BD40A3AD48-
Identifierhttp://ieeexplore.ieee.org/xpl/login.jsp?tp=&arnumber=175733&url=http%3A%2F%2Fieeexplore.ieee.org%2Fiel4%2F78%2F4466%2F00175733.pdf%3Farnumber%3D175733-
Identifierhttps://doi.org/10.1109/78.175733-
Languageen-
Extent12 pagesen
TitleFast algorithms for phone classification and recognition using segment-based modelsen
CreatorDigalakis Vasilisen
CreatorΔιγαλακης Βασιληςel
CreatorOstendorf M.en
CreatorRohlicek J. R.en
PublisherInstitute of Electrical and Electronics Engineersen
Content SummaryMethods for reducing the computation requirements of joint segmentation and recognition of phones using the stochastic segment model are presented. The approach uses a fast segment classification method that reduces computation by a factor of two to four, depending on the confidence of choosing the most probable model. A split-and-merge segmentation algorithm is proposed as an alternative to the typical dynamic programming solution of the segmentation and recognition problem, with computation savings increasing proportionally with model complexity. Although the current recognizer uses context-independent phone models, the results reported for the TIMIT database for speaker-independent joint segmentation and recognition are comparable to those of systems that use context informationen
Type of ItemPeer-Reviewed Journal Publicationen
Type of ItemΔημοσίευση σε Περιοδικό με Κριτέςel
Licensehttp://creativecommons.org/licenses/by/4.0/en
Date of Item2015-11-02-
Date of Publication1992-
SubjectSpeech recognitionen
Bibliographic CitationV. Digalakis, M. Ostendorf and J. R. Rohlicek, "Fast algorithms for phone classification and recognition using segment-based models," IEEE Trans. Signal Process., vol. 40, no. 12, pp. 2885-2896, Dec. 1992. doi:10.1109/78.175733en

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