Identifying Concatenation Discontinuities by Hierarchical Divisive Clustering of Pitch Contours
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F49777513%3A23520%2F11%3A43898189" target="_blank" >RIV/49777513:23520/11:43898189 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.1007/978-3-642-23538-2_22" target="_blank" >http://dx.doi.org/10.1007/978-3-642-23538-2_22</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-642-23538-2_22" target="_blank" >10.1007/978-3-642-23538-2_22</a>
Alternative languages
Result language
angličtina
Original language name
Identifying Concatenation Discontinuities by Hierarchical Divisive Clustering of Pitch Contours
Original language description
In this paper, we present the results of a clustering experiment, the aim of which was to show whether or not the proximity of pitch contours is sufficient condition for perceptually smooth transitions at concatenation points in concatenative speech synthesis. The experiment was motivated by a previous finding which had shown that the support vector machine (SVM) classifiers are capable of separating with a high accuracy perceptually continuous and discontinuous joins using the pitch contours extractedfrom the vicinity of concatenation points as predictors. The experiment has shown that clustering of observations in a form of pitch contours represented in different scales using the euclidean distance as a metric does not prove to be a reliable way ofidentifying discontinuities at concatenation points.
Czech name
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Czech description
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Classification
Type
J<sub>x</sub> - Unclassified - Peer-reviewed scientific article (Jimp, Jsc and Jost)
CEP classification
JD - Use of computers, robotics and its application
OECD FORD branch
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Result continuities
Project
Result was created during the realization of more than one project. More information in the Projects tab.
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach
Others
Publication year
2011
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Lecture Notes in Artificial Intelligence
ISSN
0302-9743
e-ISSN
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Volume of the periodical
2011
Issue of the periodical within the volume
6836
Country of publishing house
DE - GERMANY
Number of pages
8
Pages from-to
171-178
UT code for WoS article
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EID of the result in the Scopus database
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