ON THE USE OF GRAPHEME MODELS FOR SEARCHING IN LARGE SPOKEN ARCHIVES

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14330%2F18%3A00100802" target="_blank" >RIV/00216224:14330/18:00100802 - isvavai.cz</a>

Nalezeny alternativní kódy

RIV/49777513:23520/18:43952766

Výsledek na webu

<a href="http://dx.doi.org/10.1109/ICASSP.2018.8461774" target="_blank" >http://dx.doi.org/10.1109/ICASSP.2018.8461774</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/ICASSP.2018.8461774" target="_blank" >10.1109/ICASSP.2018.8461774</a>

Jazyk výsledku

angličtina

Název v původním jazyce

ON THE USE OF GRAPHEME MODELS FOR SEARCHING IN LARGE SPOKEN ARCHIVES

Popis výsledku v původním jazyce

This paper explores the possibility to use grapheme-based word and sub-word models in the task of spoken term detection (STD). The usage of grapheme models eliminates the need for expert-prepared pronunciation lexicons (which are often far from complete) and/or trainable grapheme-to-phoneme (G2P) algorithms that are frequently rather inaccurate, especially for rare words (words coming from a different language). Moreover, the G2P conversion of the search terms that need to be performed on-line can substantially increase the response time of the STD system. Our results show that using various grapheme-based models, we can achieve STD performance (measured in terms of ATWV) comparable with phoneme-based models but without the additional burden of G2P conversion.

Název v anglickém jazyce

ON THE USE OF GRAPHEME MODELS FOR SEARCHING IN LARGE SPOKEN ARCHIVES

Popis výsledku anglicky

This paper explores the possibility to use grapheme-based word and sub-word models in the task of spoken term detection (STD). The usage of grapheme models eliminates the need for expert-prepared pronunciation lexicons (which are often far from complete) and/or trainable grapheme-to-phoneme (G2P) algorithms that are frequently rather inaccurate, especially for rare words (words coming from a different language). Moreover, the G2P conversion of the search terms that need to be performed on-line can substantially increase the response time of the STD system. Our results show that using various grapheme-based models, we can achieve STD performance (measured in terms of ATWV) comparable with phoneme-based models but without the additional burden of G2P conversion.

Druh

D - Stať ve sborníku

CEP obor

—

OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt

<a href="/cs/project/GBP103%2F12%2FG084" target="_blank" >GBP103/12/G084: Centrum pro multi-modální interpretaci dat velkého rozsahu</a><br>

Návaznosti

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

Rok uplatnění

2018

Kód důvěrnosti údajů

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

Název statě ve sborníku

43rd IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2018)

ISBN

9781538646588

ISSN

1520-6149

e-ISSN

—

Počet stran výsledku

5

Strana od-do

6259-6263

Název nakladatele

IEEE Computer Society

Místo vydání

Neuveden

Místo konání akce

Calgary, Canada

Datum konání akce

1. 1. 2018

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

000446384606084