Prosodic Words Prediction from Lexicon Words with CRF and TBL Joint Method

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原文链接

NETL

外文摘要：Predicting prosodic words boundaries will directly influence the naturalness of synthetic speech， because prosodic word is at the lowest level of prosody hierarchy。 In this paper， a Chinese prosodic phrasing method based on CRF and TBL model is proposed。 First a CRF model is trained to predict the prosodic words boundaries from lexicon words。 After that we apply a TBL based error driven learning approach to refine the results。 The experiments shows that this joint method performs much better than HMM。

外文关键词：

prosodic wordslexicon wordsCRFTBL

作者：

Heng Kang、Wenju Liu

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作者单位：

National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences

会议名称：

International Symposium on Chinese Spoken Language Processing(ISCSLP 2006)

会议地点：

Singapore(SG)

会议母体文献：

Chinese Spoken Language Processing; Lecture Notes in Artificial Intelligence; 4274

页码：

161-168

出版时间：

2006