Detailed Information on Publication Record
2002
Symbolic Segment Dissimilarity Measure and Its Applications in Speech Synthesis
BATŮŠEK, RobertBasic information
Original name
Symbolic Segment Dissimilarity Measure and Its Applications in Speech Synthesis
Name (in English)
Symbolic Segment Dissimilarity Measure and Its Applications in Speech Synthesis
Authors
BATŮŠEK, Robert (203 Czech Republic, guarantor)
Edition
Santa Monica, USA, Proceedings of IEEE Workshop on Speech Synthesis, p. 1-4, 2002
Publisher
UCLA
Other information
Language
Czech
Type of outcome
Stať ve sborníku
Field of Study
20206 Computer hardware and architecture
Country of publisher
United States of America
Confidentiality degree
není předmětem státního či obchodního tajemství
RIV identification code
RIV/00216224:14330/02:00006531
Organization unit
Faculty of Informatics
UT WoS
000185236800032
Keywords in English
speech synthesis; segment dissimilarity
Změněno: 15/5/2003 09:42, Mgr. Robert Batůšek
V originále
This paper presents a novel method for determining a measure of dissimilarity of symbolic representations of speech segments. It is supposed that these symbolic representations can be completely derived from text, e.g. using a text analysis component of a text-to-speech synthesiser. An analysis is made to evaluate the correspondence of the particular symbolic features with the acoustic variability. A final dissimilarity measure is designed so that to maximise the correspondence with the selected acoustic measure. The designed measure is applied to the problem of sentence selection for the speech synthesis voice databases.
In English
This paper presents a novel method for determining a measure of dissimilarity of symbolic representations of speech segments. It is supposed that these symbolic representations can be completely derived from text, e.g. using a text analysis component of a text-to-speech synthesiser. An analysis is made to evaluate the correspondence of the particular symbolic features with the acoustic variability. A final dissimilarity measure is designed so that to maximise the correspondence with the selected acoustic measure. The designed measure is applied to the problem of sentence selection for the speech synthesis voice databases.
Links
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