Cost-Efficient Development of Acoustic Models for Speech Recognition of Related Languages

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Show simple item record Nouza, Jan Červa, Petr Kuchařová, Michaela 2016-05-24 2016-05-24 2013
dc.identifier.issn 1210-2512
dc.description.abstract When adapting an existing speech recognition system to a new language, major development costs are associated with the creation of an appropriate acoustic model (AM). For its training, a certain amount of recorded and annotated speech is required In this paper, we show that not only the annotation process, but also the process of speech acquisition can be automated to minimize the need of human and expert work. We demonstrate the proposed methodology on Croatian language, for which the target AM has been built via cross-lingual adaptation of a Czech AM in 2 ways: a) using the commercially available GlobalPhone database, and b) by automatic speech data mining from HRT radio archive. The latter approach is cost-free, yet it yields comparable or better results in experiments conducted on 3 Croatian test sets. en
dc.description.sponsorship Czech Science Foundation [P103/11/P499]; Technology Agency of the Czech Republic [TA01011204]
dc.format text
dc.language.iso en
dc.publisher Spolecnost Pro Radioelektronicke Inzenyrstvi
dc.publisher Technická Univerzita v Liberci cs
dc.publisher Technical university of Liberec, Czech Republic en
dc.relation.ispartof Radioengineering en
dc.source j-scopus
dc.source j-wok
dc.subject Speech recognition en
dc.subject acoustic model en
dc.subject cross-lingual adaptation en
dc.subject Slavic languages en
dc.title Cost-Efficient Development of Acoustic Models for Speech Recognition of Related Languages en
dc.type Article
local.relation.volume 22
local.relation.issue 3
local.identifier.wok 324900200026
local.identifier.scopus 2-s2.0-84885810392
local.faculty Faculty of Mechatronics, Informatics and Interdisciplinary Studies
local.citation.spage 866
local.citation.epage 873
local.identifier.stag RIV/46747885:24220/13:#0002793
local.access open
local.fulltext yes

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