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Automatic detection and classificati...

Rosenberg, Andrew.

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Automatic detection and classification of prosodic events.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Automatic detection and classification of prosodic events./
作者:	Rosenberg, Andrew.
面頁冊數:	381 p.
附註:	Source: Dissertation Abstracts International, Volume: 71-02, Section: B, page: 1119.
Contained By:	Dissertation Abstracts International71-02B.
標題:	Computer science. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3393597
ISBN:	9781109604726

Automatic detection and classification of prosodic events.
Rosenberg, Andrew.

Automatic detection and classification of prosodic events. - 381 p.

Source: Dissertation Abstracts International, Volume: 71-02, Section: B, page: 1119.

Thesis (Ph.D.)--Columbia University, 2009.

Prosody, or intonation, is a critically important component of spoken communication. The automatic extraction of prosodic information is necessary for machines to process speech with human levels of proficiency. In this thesis we describe work on the automatic detection and classification of prosodic events---specifically, pitch accents and prosodic phrase boundaries. We present novel techniques, feature representations and state of the art performance in each of these tasks. We also present three proof-of-concept applications---speech summarization, story segmentation and non-native speech assessment---showing that access to hypothesized prosodic event information can be used to improve the performance of downstream spoken language processing tasks. We believe the contributions of this thesis advance the understanding of prosodic events and the use of prosody in spoken language processing towards the goal of human-like processing of speech by machines.

ISBN: 9781109604726Subjects--Topical Terms:

523869
Computer science.

Automatic detection and classification of prosodic events.
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520 $a Prosody, or intonation, is a critically important component of spoken communication. The automatic extraction of prosodic information is necessary for machines to process speech with human levels of proficiency. In this thesis we describe work on the automatic detection and classification of prosodic events---specifically, pitch accents and prosodic phrase boundaries. We present novel techniques, feature representations and state of the art performance in each of these tasks. We also present three proof-of-concept applications---speech summarization, story segmentation and non-native speech assessment---showing that access to hypothesized prosodic event information can be used to improve the performance of downstream spoken language processing tasks. We believe the contributions of this thesis advance the understanding of prosodic events and the use of prosody in spoken language processing towards the goal of human-like processing of speech by machines.
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