Study of Prominence Detection Based on Various Phone-Specific Features
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概要
- 論文の詳細を見る
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.
- （社）電子情報通信学会の論文
- 2010-08-01
著者
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KIM Nam
School of Electrical and Computer Engineering, Chungbuk National University
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Kim Sung
School Of Dentistry Kyunghee University
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Kim Nam
Seoul National Univ. Seoul Kor
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Han Chang
School Of Electrical Engineering And The Institute Of New Media And Communications Seoul National Un
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Kim Sung
School Of Computer Science And Engineering Chung-ang University
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Kim Sung
School Of Electrical Engineering And The Institute Of New Media And Communications Seoul National Un
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Kim Nam
School Of Electrical Engineering And The Institute Of New Media And Communications Seoul National Un
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Kim Nam
School Of Electrical And Computer Engineering Chungbuk National University
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Kim Sung
School Of Computer Sci. And Engineering Chung-ang Univ.
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Kim Nam
School Of Electrical And Computer Engineering Chungbuk National Univ.
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HAN Chang
School of Electrical Engineering and the INMC, Seoul National University
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KIM Nam
School of Architecture and Architectural Engineering, Korea University of Technology and Education
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