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Nucleus-level clustering for word-independent syllable stress classification
- Source :
-
Speech Communication . Dec2009, Vol. 51 Issue 12, p1224-1233. 10p. - Publication Year :
- 2009
-
Abstract
- Abstract: This paper presents a word-independent technique for classifying the syllable stress of spoken English words. The proposed technique improves upon the existing word-independent techniques by utilizing the acoustic differences of various syllable nuclei. Syllables with acoustically similar nuclei are grouped together and a separate stress classifier is trained for each such group. The performance of the proposed group-specific classifiers is analyzed as the number of groups is increased and is also compared with an alternative data-driven clustering based approach. The proposed technique improves the syllable-level accuracy by 5.2% and the word-level accuracy by 1.1%. The corresponding improvements using the data-driven clustering based approach are 0.12% and 0.02%, respectively. [Copyright &y& Elsevier]
Details
- Language :
- English
- ISSN :
- 01676393
- Volume :
- 51
- Issue :
- 12
- Database :
- Academic Search Index
- Journal :
- Speech Communication
- Publication Type :
- Academic Journal
- Accession number :
- 44173441
- Full Text :
- https://doi.org/10.1016/j.specom.2009.06.006