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Author Stemmer, Georg, author
Title Modeling variability in speech recognition / Georg Stemmer
Imprint Berlin : Logos Verlag, [2005]
book jacket
LOCATION CALL # STATUS OPACMSG BARCODE
 人文社會聯圖  TK7882.S65 S746 2005    AVAILABLE    30630020094494
Descript vi, 261 pages : illustrations ; 21 cm
text txt rdacontent
unmediated n rdamedia
volume nc rdacarrier
Series Studien zur Mustererkennung, 1617-0695 ; Band 19
Studien zur Mustererkennung ; Bd. 19
Note "Submitted to the Technische Fakultät der Universität Erlangen-Nurnberg in partial fulfillment of the erquirements for the degree of DOKTOR-INGENIEUR of Georg Stemmer, Erlangen 2005"
Thesis (Ph. D.)--Erlangen-Nurnberg University, 2005
Includes bibliographical references (p. 193-216) and index
A major challenge in automatic speech recognition is to achieve good results in tasks where the spoken input is highly variable due to frequent changes of the speaker or of the acoustic conditions. For instance, spoken dialog systems that are connected to the public phone network have to cope with various non-native accents, dialects, speakers of different ages, low-volume speech and varying signal quality. In this work a combination of several approaches is proposed to increase robustness of a speech recognizer. For recognition of children's speech and non-native speech suitable adaptation and normalization methods are developed. Integration of acoustic and linguistic context into the models of the speech recognizer leads to improvements also for those sources of variability that have not or only seldom been observed in the training data. Experimental results are reported for several different data sets, including collections of non-native German and English speech, speech that has been recorded with a spoken dialog system and children's speech
Subject Automatic speech recognition
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