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Jáchym Kolář and Yang Liu : Comparing and Combining Modeling Techniques for Sentence Segmentation of Spoken Czech Using Textual and Prosodic Information . Proc. of Speech Prosody, Chicago, IL, USA, 2010.

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Abstract

This paper deals with automatic sentence boundary detection in spoken Czech using both textual and prosodic information. This task is important to make automatic speech recognition (ASR) output more readable and easier for downstream language processing modules. We compare and combine three statistical models – hidden Markov model, maximum entropy, and adaptive boosting. We evaluate these methods on two Czech corpora, broadcast news and broadcast conversations, using both manual and ASR transcripts. Our results show that superior results are achieved when all the three models are combined via posterior probability interpolation, and that there is substantial difference among the three methods when using different knowledge sources, as well as in different genres. Feature analysis also reveals significant differences in prosodic feature usage patterns between the two genres.

Detail of publication

Title: Comparing and Combining Modeling Techniques for Sentence Segmentation of Spoken Czech Using Textual and Prosodic Information
Author: Jáchym Kolář ; Yang Liu
Language: English
Date of publication: 11 May 2010
Year: 2010
Type of publication: Papers in journals
Book title: Proc. of Speech Prosody
Address: Chicago, IL, USA
Date: 11 May 2010 - 14 May 2010
/ 2011-03-15 18:43:01 /

Keywords

sentence segmentation, prosody, HMM, maximum entropy, boosting

BibTeX

@INPROCEEDINGS{JachymKolar_2010_Comparingand,
 author = {J\'{a}chym Kol\'{a}\v{r} and Yang Liu},
 title = {Comparing and Combining Modeling Techniques for Sentence Segmentation of Spoken Czech Using Textual and Prosodic Information},
 year = {2010},
 address = {Chicago, IL, USA},
 booktitle = {Proc. of  Speech Prosody},
 url = {http://www.kky.zcu.cz/en/publications/JachymKolar_2010_Comparingand},
}