Detecting artifacts in synthetic speech

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F49777513%3A23520%2F15%3A43926635" target="_blank" >RIV/49777513:23520/15:43926635 - isvavai.cz</a>

Výsledek na webu

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DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

Detecting artifacts in synthetic speech

Popis výsledku v původním jazyce

Nowadays, speech synthesis is growing very popular in everyday use. For example, automatic voice assistants on mobile platforms are getting smarter every year, using speech synthesis and speech recognition to communicate with the user in a more natural way. As more people make use of speech synthesis, the quality requirements are higher more than ever. Although scientists currently focus mainly on HMM-based synthesis, real applications still use the traditional unit-selection method. Unit selection is known for its ability to produce high-quality synthetic speech. It produces more natural speech, but it may suffer from sudden quality drops at concatenation points. Quality drops ("artifacts") can theoretically occur at every concatenation point. In thefollowing paragraphs, an experiment on the automatic detection of artifacts in concatenation speech synthesis is presented. The main goal was to build a classifier which would mark suspicious segments in synthetic speech in the same way a

Název v anglickém jazyce

Detecting artifacts in synthetic speech

Popis výsledku anglicky

Nowadays, speech synthesis is growing very popular in everyday use. For example, automatic voice assistants on mobile platforms are getting smarter every year, using speech synthesis and speech recognition to communicate with the user in a more natural way. As more people make use of speech synthesis, the quality requirements are higher more than ever. Although scientists currently focus mainly on HMM-based synthesis, real applications still use the traditional unit-selection method. Unit selection is known for its ability to produce high-quality synthetic speech. It produces more natural speech, but it may suffer from sudden quality drops at concatenation points. Quality drops ("artifacts") can theoretically occur at every concatenation point. In thefollowing paragraphs, an experiment on the automatic detection of artifacts in concatenation speech synthesis is presented. The main goal was to build a classifier which would mark suspicious segments in synthetic speech in the same way a

Druh

C - Kapitola v odborné knize

CEP obor

JD - Využití počítačů, robotika a její aplikace

OECD FORD obor

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Projekt

<a href="/cs/project/ED1.1.00%2F02.0090" target="_blank" >ED1.1.00/02.0090: NTIS - Nové technologie pro informační společnost</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2015

Kód důvěrnosti údajů

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

Název knihy nebo sborníku

Tackling the Complexity in Speech

ISBN

978-80-7308-558-2

Počet stran výsledku

10

Strana od-do

195-204

Počet stran knihy

230

Název nakladatele

Univerzita Karlova v Praze

Místo vydání

Praha

Kód UT WoS kapitoly

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