GlobalPhone: A multilingual text &amp;amp; speech database in 20 languages

Schultz, Tanja; Vu, Ngoc Thang; Schlippe, Tim

doi:10.1109/icassp.2013.6639248

Cited by 84 publications

(61 citation statements)

References 3 publications

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“…If such data is available, experiments to cross-language synthesis are reported using the cross-lingual databases. Such speech databases includes the speech data, where multiple speakers, who are capable of speaking more than one language are recorded [19]. In such circumstance authors tested a state-mapping approach [20], where the main task is to find the state similarities of average voice-language-dependent acoustic models [17].…”

Section: Related Workmentioning

confidence: 99%

Towards automatic cross-lingual acoustic modelling applied to HMM-based speech synthesis for under-resourced languages

Justin

Žibert

2016

Automatika

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Original scientific paperNowadays Human Computer Interaction (HCI) can also be achieved with voice user interfaces (VUIs). To enable devices to communicate with humans by speech in the user's own language, low-cost language portability is often discussed and analysed. One of the most time-consuming parts for the language-adaptation process of VUIcapable applications is the target-language speech-data acquisition. Such data is further used in the development of VUIs subsystems, especially of speech-recognition and speech-production systems. The tempting idea to bypass a long-term process of data acquisition is considering the design and development of an automatic algorithms, which can extract the similar target-language acoustic from different language speech databases. This paper focus on the cross-lingual phoneme mapping between an under-resourced and a well-resourced language. It proposes a novel automatic phoneme-mapping technique that is adopted from the speaker-verification field. Such a phoneme mapping is further used in the development of the HMM-based speech-synthesis system for the under-resourced language. The synthesised utterances are evaluated with a subjective evaluation and compared by the expert knowledge cross-language method against to the baseline speech synthesis based just from the under-resourced data. The results reveals, that combining data from well-resourced and under-resourced language with the use of the proposed phoneme-mapping technique, can improve the quality of under-resourced language speech synthesis.Key words: Voice user interfaces, Human language technologies, HMM-based speech synthesis, Cross-language synthesis, Under-resourced languages, UBM-MAP-GMM phoneme mapping Primjena automatskog medujezičnog akustičnog modeliranja na HMM sintezu govora za oskudne jezične baze. U današnje vrijeme interakcijačovjeka i računala (HCI) može se ostvariti i putem govornih sučelja (VUIs). Da bi se omogućila komunikacija uredaja i korisnika putem govora na vlastitom korisnikovom jeziku, cesto se raspravlja i analizira o jeftinom rješenju prijevoda govora na različite jezike. Jedan od vremenski najzahtjevnijih dijelova procesa prilagodbe jezika za aplikacije koje podržavaju VUI je prikupljanje govornih podataka za ciljani jezik. Ovakvi podaci dalje se koriste za razvoj VUI podsustava, posebice za prepoznavanje i produkciju govora. Primamljiva ideja za izbjegavanje dugotrajnog postupka prikupljanja podataka jeste razmatranje sinteze i razvoja automatskih algoritama koji su sposobni izvesti slična akustična svojstva za ciljani jezik iz postojećih baza različitih jezika. Ovaj rad fokusiran je na povezivanje medujezičnih fonema izmedu oskudnih i bogatih jezičnih baza. Predložena je nova tehnika automatskog povezivanja fonema, usvojena i prilagodena iz područja govorne autentikacije. Ovakvo povezivanje fonema kasnije se koristi za razvoj sustava za sintezu govora zasnovanom na HMM-u za manje poznate jezike. Načinjene govorne izjave ocijenjene su subjektivnim pristupom kroz usporedbu medujezičnih m...

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Section: Related Workmentioning

confidence: 99%

Towards automatic cross-lingual acoustic modelling applied to HMM-based speech synthesis for under-resourced languages

Justin

Žibert

2016

Automatika

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“…Citons également ILPho (Boula De Mareuil et al, 2000), plus récente, créée en complétant les entrées du lexique morphosyntaxique Multext (Ide et Véronis, 1994) par des transcriptions phonémiques. Enfin, GlobalPhone (Schultz et al, 2013) est une base de données comprenant des dictionnaires de prononciation, dont la première version date de 2002. Ces dictionnaires ont été produits automatiquement par des outils entraînés sur des transcriptions d'enregistrements de locuteurs et les textes correspondants, puis corrigés manuellement.…”

Section: Ressources Lexicales : Une Situation Insatisfaisanteunclassified

Ne jetons pas le Wiktionnaire avec l'oripeau du Web ! Etudes et réalisations fondées sur le dictionnaire collaboratif

Sajous

Hathout

Calderone

2014

SHS Web of Conferences

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“…To simulate resource-poor scenario for the Romanian-English language pair, we sample a parallel corpus of same size from the transcribed TED talks (Cettolo et al, 2012). To evalu-4 For Arabic and French we use the GlobalPhone pronunciation dictionaries (Schultz et al, 2013) (we manually convert them to IPA). For Swahili and Romanian we automatically construct pronunciation dictionaries using the Omniglot grapheme-to-IPA conversion rules at www.omniglot.com.…”

Section: Methodsmentioning

confidence: 99%

Lexicon Stratification for Translating Out-of-Vocabulary Words

Tsvetkov

Dyer

2015

Proceedings of the 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Confere

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A language lexicon can be divided into four main strata, depending on origin of words: core vocabulary words, fully-and partiallyassimilated foreign words, and unassimilated foreign words (or transliterations). This paper focuses on translation of fullyand partially-assimilated foreign words, called "borrowed words". Borrowed words (or loanwords) are content words found in nearly all languages, occupying up to 70% of the vocabulary. We use models of lexical borrowing in machine translation as a pivoting mechanism to obtain translations of out-of-vocabulary loanwords in a lowresource language. Our framework obtains substantial improvements (up to 1.6 BLEU) over standard baselines.

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GlobalPhone: A multilingual text & speech database in 20 languages

Cited by 84 publications

References 3 publications

Towards automatic cross-lingual acoustic modelling applied to HMM-based speech synthesis for under-resourced languages

Towards automatic cross-lingual acoustic modelling applied to HMM-based speech synthesis for under-resourced languages

Ne jetons pas le Wiktionnaire avec l'oripeau du Web ! Etudes et réalisations fondées sur le dictionnaire collaboratif

Lexicon Stratification for Translating Out-of-Vocabulary Words

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