Listening-test-based annotation of communicative functions for expressive speech synthesis

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F49777513%3A23520%2F10%3A00504219" target="_blank" >RIV/49777513:23520/10:00504219 - isvavai.cz</a>

Result on the web

—

DOI - Digital Object Identifier

—

Result language

angličtina

Original language name

Listening-test-based annotation of communicative functions for expressive speech synthesis

Original language description

This paper is focused on the evaluation of listening test that was realized with a view to objectively annotate expressive speech recordings and further develop a limited domain expressive speech synthesis system. There are two main issues to face in this task. The first matter in issue to be taken into consideration is the fact that expressivity in speech has to be defined in some way. The second problem is that perception of expressive speech is a subjective question. However, for the purposes of expressive speech synthesis using unit selection algorithms, the expressive speech corpus has to be objectively and unambiguously annotated. At first, a classification of expressivity was determined making use of communicative functions. These are supposed to describe the type of expressivity and/or speaker?s attitude. Further, to achieve objectivity at a significant level, a listening test with relatively high number of listeners was realized. The listeners were asked to mark sentences in t

Czech name

—

Czech description

—

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

—

Project

<a href="/en/project/GA102%2F09%2F0989" target="_blank" >GA102/09/0989: New innovative methods for high-quality synthesis of Czech speech</a><br>

Continuities

S - Specificky vyzkum na vysokych skolach

Publication year

2010

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

—

Volume of the periodical

2010

Issue of the periodical within the volume

6231

Country of publishing house

DE - GERMANY

Number of pages

8

Pages from-to

—

UT code for WoS article

—

EID of the result in the Scopus database

—