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A study of meta-linguistic features ...

Wang, Dagen.

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A study of meta-linguistic features in spontaneous speech processing .

Record Type:	Language materials, printed : Monograph/item
Title/Author:	A study of meta-linguistic features in spontaneous speech processing ./
Author:	Wang, Dagen.
Description:	141 p.
Notes:	Adviser: Shrikanth Narayanan.
Contained By:	Dissertation Abstracts International67-10B.
Subject:	Engineering, Electronics and Electrical. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3237175
ISBN:	9780542912818

A study of meta-linguistic features in spontaneous speech processing .
Wang, Dagen.

A study of meta-linguistic features in spontaneous speech processing . - 141 p.

Adviser: Shrikanth Narayanan.

Thesis (Ph.D.)--University of Southern California, 2006.

Lastly, we use all the above features to study speech acts detection, specifically distinguishing between wh-questions and statements. The prominence of first two syllables and their timings are found to be useful for such task.

ISBN: 9780542912818Subjects--Topical Terms:

626636
Engineering, Electronics and Electrical.

A study of meta-linguistic features in spontaneous speech processing .
LDR:03053nam 2200313 a 45 001 965325
005 20110906
008 110906s2006 eng d
020 $a 9780542912818
035 $a (UnM)AAI3237175
035 $a AAI3237175
040 $a UnM $c UnM
100 1 $a Wang, Dagen. $3 1288100
245 1 2 $a A study of meta-linguistic features in spontaneous speech processing .
300 $a 141 p.
500 $a Adviser: Shrikanth Narayanan.
500 $a Source: Dissertation Abstracts International, Volume: 67-10, Section: B, page: 5970.
502 $a Thesis (Ph.D.)--University of Southern California, 2006.
520 $a Lastly, we use all the above features to study speech acts detection, specifically distinguishing between wh-questions and statements. The prominence of first two syllables and their timings are found to be useful for such task.
520 $a Speech is a crucial component in human computer interaction. While tremendous progress has been made in automatic speech recognition, speech transcription, which is the output of automatic speech recognition, is far from providing all the information that one could retrieve from speech. For example, prominence, rate of speech all carry important information in speech and are crucial to speech perception. Inclusion of such meta-linguistic features can facilitate better machine recognition and understanding of speech. In this thesis, we illustrate various research progress in study of the meta-linguistic features.
520 $a Firstly, we proposed an acoustic measure of speech rate without speech recognition. It includes various spectral, temporal and smoothing algorithms to identify the syllable nucleus, which is easily converted to speech rate measure by dividing the length of speech. The parameters of the algorithm is optimized by Monte-Carlo simulation followed by a sensitivity analysis.
520 $a Secondly, we extend the syllable nucleus estimation algorithm to provide an acoustic measure of prominence. It fuses features such as syllable duration, spectral intensity and pitch patterns to score prominence on a continuous scale. We proposed parametric shape based features to identify the pitch shape and demonstrate its usefulness in prominence detection. Beyond direct evaluation on manually transcribed prominence, linguistic correlation with part of speech was used to measure prominence.
520 $a Thirdly, we use rate and prominence feature and many other acoustic features to automatically detect utterance boundary and disfluency. We extract features from pitch breaks and their surrounding regions. Such process includes a piecewise linear stylization of pitch coutour. A rule based approach and a machine learning approach are proposed and compared on various boundary and disfluency events.
590 $a School code: 0208.
650 4 $a Engineering, Electronics and Electrical. $3 626636
690 $a 0544
710 2 0 $a University of Southern California. $3 700129
773 0 $t Dissertation Abstracts International $g 67-10B.
790 $a 0208
790 1 0 $a Narayanan, Shrikanth, $e advisor
791 $a Ph.D.
792 $a 2006
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3237175