Iterative Grapheme-to-Phoneme Alignment for the Training of WFST-based Phonetic Conversion

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F46747885%3A24220%2F13%3A%230002794" target="_blank" >RIV/46747885:24220/13:#0002794 - isvavai.cz</a>

Nalezeny alternativní kódy

RIV/46747885:24220/13:#0002593

Výsledek na webu

<a href="http://dx.doi.org/10.1109/TSP.2013.6613977" target="_blank" >http://dx.doi.org/10.1109/TSP.2013.6613977</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/TSP.2013.6613977" target="_blank" >10.1109/TSP.2013.6613977</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Iterative Grapheme-to-Phoneme Alignment for the Training of WFST-based Phonetic Conversion

Popis výsledku v původním jazyce

In this paper we propose an algorithm for graphemeto-phoneme (G2P) alignment. Such alignment is needed mainly for the data-driven training of G2P conversion tools. Our approach utilizes a given phonetic alphabet and a set of given orthographic-phonetic word pairs as a source of prior knowledge. The development data are taken from a manually created pronunciation lexicon for a large vocabulary speech recognition system for Czech. The alignment method is based on extended Minimum Edit Distance algorithm.Moreover, we propose an approach to avoid the creation of reference alignments ? we evaluate the improvements through a specially designed G2P converter, i.e. we compare the phonetic transcription directly to a set of test orthographic-phonetic word pairs. Results of our approach are comparable or even slightly better than the state-of-the-art.

Název v anglickém jazyce

Iterative Grapheme-to-Phoneme Alignment for the Training of WFST-based Phonetic Conversion

Popis výsledku anglicky

In this paper we propose an algorithm for graphemeto-phoneme (G2P) alignment. Such alignment is needed mainly for the data-driven training of G2P conversion tools. Our approach utilizes a given phonetic alphabet and a set of given orthographic-phonetic word pairs as a source of prior knowledge. The development data are taken from a manually created pronunciation lexicon for a large vocabulary speech recognition system for Czech. The alignment method is based on extended Minimum Edit Distance algorithm.Moreover, we propose an approach to avoid the creation of reference alignments ? we evaluate the improvements through a specially designed G2P converter, i.e. we compare the phonetic transcription directly to a set of test orthographic-phonetic word pairs. Results of our approach are comparable or even slightly better than the state-of-the-art.

Druh

D - Stať ve sborníku

CEP obor

JC - Počítačový hardware a software

OECD FORD obor

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Projekt

<a href="/cs/project/TA01011204" target="_blank" >TA01011204: Živé archivy</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

2013

Kód důvěrnosti údajů

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

Název statě ve sborníku

Proc. of 36th International Conference on Telecommunications and Signal Processing (TSP 2013)

ISBN

9781479904044

ISSN

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e-ISSN

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Počet stran výsledku

5

Strana od-do

474-478

Název nakladatele

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Místo vydání

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Místo konání akce

Itálie

Datum konání akce

1. 1. 2013

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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