Název:	Comparing and combining modeling techniques for sentence segmentation of spoken czech using textual and prosodic information
Autoři:	Kolář, Jáchym Liu, Yang
Citace zdrojového dokumentu:	KOLÁŘ, Jáchym; LIU, Yang. Comparing and combining modeling techniques for sentence segmentation of spoken czech using textual and prosodic information. In: Proceeding of conference Speech prosody 2010, 11th-14th May 2010, Chicago, USA. Chicago: University of Illionois, 2010, p. [1-4].
Datum vydání:	2010
Nakladatel:	University of Illionois
Typ dokumentu:	článek article
URI:	http://www.kky.zcu.cz/cs/publications/JachymKolar_2010_Comparingand http://hdl.handle.net/11025/17173
Klíčová slova:	segmentace vět;prozodie;HMM;maximální entropie;posílení
Klíčová slova v dalším jazyce:	sentence segmentation;prosody;HMM;maximum entropy;boosting
Abstrakt v dalším jazyce:	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.
Práva:	© Jáchym Kolář - Yang Liu
Vyskytuje se v kolekcích:	Články / Articles (KKY)

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