IEICE Transactions on Information and Systems
Online ISSN : 1745-1361
Print ISSN : 0916-8532
Regular Section
Study of Prominence Detection Based on Various Phone-Specific Features
Sung Soo KIMChang Woo HANNam Soo KIM
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Volume E93.D (2010) Issue 8 Pages 2327-2330

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Abstract

In this letter, we present useful features accounting for pronunciation prominence and propose a classification technique for prominence detection. A set of phone-specific features are extracted based on a forced alignment of the test pronunciation provided by a speech recognition system. These features are then applied to the traditional classifiers such as the support vector machine (SVM), artificial neural network (ANN) and adaptive boosting (Adaboost) for detecting the place of prominence.

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© 2010 The Institute of Electronics, Information and Communication Engineers
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