Institutional Repository
Technical University of Crete
Technical University of Crete
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| URI: | http://purl.tuc.gr/dl/dias/E2EA7355-151C-41CB-BE98-13BD40A3AD48 | ||
| Year | 1992 | ||
| Type of Item | Peer-Reviewed Journal Publication | ||
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| Bibliographic Citation | V. 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:10.1109/78.175733 https://doi.org/10.1109/78.175733 | ||
| Appears in Collections |
Methods 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 information
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