Difference between revisions of "Bartlett et al., ACL-HLT 2008. Automatic Syllabification with Structured SVMs for Letter-to-Phoneme Conversion"
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== Summary == | == Summary == | ||
| + | This [[Category::paper]] describes one of the first successful attempts at integrating automatic syllabification into a letter-to-phoneme conversion system using structured [[UsesMethod::Support_Vector_Machines | SVMs]]. The authors obtain substantial improvements in reducing automatic syllabification error rate (measured in WER) against the then state-of-the-art approach. The authors model the problem as an orthographic syllabification task as opposed to phonological syllabification. They treat it as a sequence tagging problem and define new tagging schemes. The method is applied to languages such as German and Dutch, in addition to English. | ||
== Method == | == Method == | ||
Revision as of 17:39, 25 September 2011
Citation
Susan Bartlett, Grzegorz Kondrak and Colin Cherry. 2008. Automatic syllabification with structured SVMs for letter-to-phoneme conversion. In Proceedings of ACL-08: HLT, 2008, pp. 568–576.
Online Version
Automatic syllabification with structured SVMs for letter-to-phoneme conversion.
Summary
This paper describes one of the first successful attempts at integrating automatic syllabification into a letter-to-phoneme conversion system using structured SVMs. The authors obtain substantial improvements in reducing automatic syllabification error rate (measured in WER) against the then state-of-the-art approach. The authors model the problem as an orthographic syllabification task as opposed to phonological syllabification. They treat it as a sequence tagging problem and define new tagging schemes. The method is applied to languages such as German and Dutch, in addition to English.
