The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. ex. Some numerals are expressed as "XNUMX".
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The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. Copyrights notice
Nesta carta, apresentamos recursos úteis para contabilizar a proeminência da pronúncia e propomos uma técnica de classificação para detecção de proeminência. Um conjunto de recursos específicos do telefone é extraído com base em um alinhamento forçado da pronúncia do teste fornecido por um sistema de reconhecimento de fala. Esses recursos são então aplicados aos classificadores tradicionais, como máquina de vetores de suporte (SVM), rede neural artificial (RNA) e reforço adaptativo (Adaboost) para detecção do local de destaque.
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Sung Soo KIM, Chang Woo HAN, Nam Soo KIM, "Study of Prominence Detection Based on Various Phone-Specific Features" in IEICE TRANSACTIONS on Information,
vol. E93-D, no. 8, pp. 2327-2330, August 2010, doi: 10.1587/transinf.E93.D.2327.
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.
URL: https://global.ieice.org/en_transactions/information/10.1587/transinf.E93.D.2327/_p
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@ARTICLE{e93-d_8_2327,
author={Sung Soo KIM, Chang Woo HAN, Nam Soo KIM, },
journal={IEICE TRANSACTIONS on Information},
title={Study of Prominence Detection Based on Various Phone-Specific Features},
year={2010},
volume={E93-D},
number={8},
pages={2327-2330},
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.},
keywords={},
doi={10.1587/transinf.E93.D.2327},
ISSN={1745-1361},
month={August},}
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TY - JOUR
TI - Study of Prominence Detection Based on Various Phone-Specific Features
T2 - IEICE TRANSACTIONS on Information
SP - 2327
EP - 2330
AU - Sung Soo KIM
AU - Chang Woo HAN
AU - Nam Soo KIM
PY - 2010
DO - 10.1587/transinf.E93.D.2327
JO - IEICE TRANSACTIONS on Information
SN - 1745-1361
VL - E93-D
IS - 8
JA - IEICE TRANSACTIONS on Information
Y1 - August 2010
AB - 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.
ER -