On the Impact of Annotation Errors on Unit-Selection Speech Synthesis

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F49777513%3A23520%2F12%3A43916071" target="_blank" >RIV/49777513:23520/12:43916071 - isvavai.cz</a>

Result on the web

<a href="http://dx.doi.org/10.1007/978-3-642-32790-2_55" target="_blank" >http://dx.doi.org/10.1007/978-3-642-32790-2_55</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/978-3-642-32790-2_55" target="_blank" >10.1007/978-3-642-32790-2_55</a>

Result language

angličtina

Original language name

On the Impact of Annotation Errors on Unit-Selection Speech Synthesis

Original language description

Unit selection is a very popular approach to speech synthesis. It is known for its ability to produce nearly natural-sounding synthetic speech, but, at the same time, also for its need for very large speech corpora. In addition, unit selection is also known to be very sensitive to the quality of the source speech corpus the speech is synthesised from and its textual, phonetic and prosodic annotations and indexation. Given the enormous size of current speech corpora, manual annotation of the corpora is alengthy process. Despite this fact, human annotators do make errors. In this paper, the impact of annotation errors on the quality of unit-selection-based synthetic speech is analysed. Firstly, an analysis and categorisation of annotation errors is presented. Then, a speech synthesis experiment, in which the same utterances were synthesised by unit-selection systems with and without annotation errors, is described. Results of the experiment and the options for fixing the annotation erro

Czech name

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Czech description

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Type

J_x - 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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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)

Publication year

2012

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical

Lecture Notes in Artificial Intelligence

ISSN

0302-9743

e-ISSN

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Volume of the periodical

2012

Issue of the periodical within the volume

7499

Country of publishing house

DE - GERMANY

Number of pages

8

Pages from-to

456-463

UT code for WoS article

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EID of the result in the Scopus database

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