Modeling of pronunciation, language and nonverbal units at conversational Russian speech recognition

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F49777513%3A23520%2F13%3A43919612" target="_blank" >RIV/49777513:23520/13:43919612 - isvavai.cz</a>

Výsledek na webu

<a href="http://www.scopus.com/record/display.url?eid=2-s2.0-84880608704&origin=resultslist&sort=plf-f&cite=2-s2.0-84872512624&src=s&imp=t&sid=7AFC1218245E269A99CAA0AC46F63467.fM4vPBipdL1BpirDq5Cw%3a190&sot=cite&sdt=a&sl=0&relpos=4&relpos=4&citeCnt=0&searchTerm=" target="_blank" >http://www.scopus.com/record/display.url?eid=2-s2.0-84880608704&origin=resultslist&sort=plf-f&cite=2-s2.0-84872512624&src=s&imp=t&sid=7AFC1218245E269A99CAA0AC46F63467.fM4vPBipdL1BpirDq5Cw%3a190&sot=cite&sdt=a&sl=0&relpos=4&relpos=4&citeCnt=0&searchTerm=</a>

DOI - Digital Object Identifier

—

Jazyk výsledku

angličtina

Název v původním jazyce

Modeling of pronunciation, language and nonverbal units at conversational Russian speech recognition

Popis výsledku v původním jazyce

The main problems of a conversational Russian speech recognition system development are variability of pronunciation, free word-order in sentences and presence of speech disfluencies. In the paper, pronunciation variability is modeled by creation of multiple word transcriptions. A syntactic statistical language model that takes into account long-distant word dependencies is proposed for Russian language modeling. Also in this paper the results of analysis of such speech disfluencies as artefacts and filled pauses, which were extracted during segmentation of the Russian speech corpus, are presented. The recognition accuracy of nonverbal elements in the collected corpus was 87%. The proposed methods of pronunciation variability modeling and syntactic-statistical language model creation were realized in the software complex for Russian speech recognition. The performed experiments with large vocabulary using syntactic-statistical language model showed that word error rate of the system wa

Název v anglickém jazyce

Modeling of pronunciation, language and nonverbal units at conversational Russian speech recognition

Popis výsledku anglicky

The main problems of a conversational Russian speech recognition system development are variability of pronunciation, free word-order in sentences and presence of speech disfluencies. In the paper, pronunciation variability is modeled by creation of multiple word transcriptions. A syntactic statistical language model that takes into account long-distant word dependencies is proposed for Russian language modeling. Also in this paper the results of analysis of such speech disfluencies as artefacts and filled pauses, which were extracted during segmentation of the Russian speech corpus, are presented. The recognition accuracy of nonverbal elements in the collected corpus was 87%. The proposed methods of pronunciation variability modeling and syntactic-statistical language model creation were realized in the software complex for Russian speech recognition. The performed experiments with large vocabulary using syntactic-statistical language model showed that word error rate of the system wa

Druh

J_x - Nezařazeno - Článek v odborném periodiku (Jimp, Jsc a Jost)

CEP obor

JD - Využití počítačů, robotika a její aplikace

OECD FORD obor

—

Projekt

<a href="/cs/project/ME08106" target="_blank" >ME08106: Vývoj integrálního multimodálního pomocného systému</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2013

Kód důvěrnosti údajů

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

Název periodika

International Journal of Computer Science and Applications

ISSN

0972-9038

e-ISSN

—

Svazek periodika

10

Číslo periodika v rámci svazku

1

Stát vydavatele periodika

IN - Indická republika

Počet stran výsledku

20

Strana od-do

11-30

Kód UT WoS článku

—

EID výsledku v databázi Scopus

—