1,802 research outputs found

    Estoñol, a computer-assisted pronunciation training tool for Spanish L1 speakers to improve the pronunciation and perception of Estonian vowels

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    Over the past few years the number of online language teaching materials for non-native speakers of Estonian has increased. However, they focus mainly on vocabulary and pay little attention to pronunciation. In this study we introduce a computerassisted pronunciation training tool, Estoñol, developed to help native speakers of Spanish to train their perception and production of Estonian vowels. The tool’s training program involves seven vowel contrasts, /i-y/, /u-y/, /ɑ-o/, /ɑ-ĂŠ/, /e-ĂŠ/, /o-Ăž/, and /o-É€/, which have proven to be difficult for native speakers of Spanish. The training activities include theoretical videos and four training modes (exposure, discrimination, pronunciation, and mixed) in every lesson. The tool is integrated into a pre/post-test design experiment with native speakers of Spanish and Estonian to assess the language learners’ perception and production improvement. It is expected that the tool will have a positive effect on the results, as has been shown in previous studies using similar methodology. KokkuvĂ”te. Katrin Leppik ja Cristian Tejedor-GarcĂ­a: Estoñol, mobiilirakendus hispaania emakeelega eesti keele Ă”ppijatele vokaalide hÀÀlduse ja taju treenimiseks. Eesti keele Ă”ppimiseks on loodud mitmeid e-kursusi ja mobiilirakendusi, kuid need keskenduvad peamiselt sĂ”navara ja gram matika Ă”petamisele ning pööravad vĂ€ga vĂ€he tĂ€helepanu hÀÀldusele. Eesti keele hÀÀlduse omandamise lihtsustamiseks töötati vĂ€lja mobiilirakendus Estoñol, mis on mĂ”eldud hispaania emakeelega eesti keele Ă”ppijatele. Varasemad uurimused on nĂ€idanud, et hispaania emakeelega eesti keele Ă”ppijatele valmistab raskusi vokaalide /ɑ, y, Ăž, ĂŠ, É€/ hÀÀldamine. Mobiilirakenduse sisu on jagatud seitsmeks peatĂŒkiks, kus on vĂ”imalik harjutada vokaalipaaride /i-y/, /u-y/, /ɑ-o/, /ɑ-ĂŠ/, /e-ĂŠ/, /o-Ăž/, /o-É€/ tajumist ja hÀÀldamist. Iga peatĂŒkk algab teoreetilise videoga, millele jĂ€rgnevad taju- ja hÀÀldusharjutused. Mobiilirakenduse mĂ”ju hindamiseks keeleĂ”ppija hÀÀldusele ja tajule plaanitakse lĂ€bi viia eksperiment. MĂ€rksĂ”nad: CAPT, eesti keel, hispaania keel, L2, hÀÀldus, taju, vokaalid, Estoño

    On the Effectiveness of Neural Text Generation based Data Augmentation for Recognition of Morphologically Rich Speech

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    Advanced neural network models have penetrated Automatic Speech Recognition (ASR) in recent years, however, in language modeling many systems still rely on traditional Back-off N-gram Language Models (BNLM) partly or entirely. The reason for this are the high cost and complexity of training and using neural language models, mostly possible by adding a second decoding pass (rescoring). In our recent work we have significantly improved the online performance of a conversational speech transcription system by transferring knowledge from a Recurrent Neural Network Language Model (RNNLM) to the single pass BNLM with text generation based data augmentation. In the present paper we analyze the amount of transferable knowledge and demonstrate that the neural augmented LM (RNN-BNLM) can help to capture almost 50% of the knowledge of the RNNLM yet by dropping the second decoding pass and making the system real-time capable. We also systematically compare word and subword LMs and show that subword-based neural text augmentation can be especially beneficial in under-resourced conditions. In addition, we show that using the RNN-BNLM in the first pass followed by a neural second pass, offline ASR results can be even significantly improved.Comment: 8 pages, 2 figures, accepted for publication at TSD 202

    Proceedings

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    Proceedings of the NODALIDA 2009 workshop Nordic Perspectives on the CLARIN Infrastructure of Language Resources. Editors: Rickard Domeij, Kimmo Koskenniemi, Steven Krauwer, Bente Maegaard, Eiríkur Rögnvaldsson and Koenraad de Smedt. NEALT Proceedings Series, Vol. 5 (2009), v+45 pp. © 2009 The editors and contributors. Published by Northern European Association for Language Technology (NEALT) http://omilia.uio.no/nealt . Electronically published at Tartu University Library (Estonia) http://hdl.handle.net/10062/9207

    Neural Text-to-Speech Synthesis for VÔro

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    Automatic Closed Captioning for Estonian Live Broadcasts

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    The role of linguistics in language teaching: the case of two, less widely taught languages - Finnish and Hungarian

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    This paper discusses the role of various linguistic sub-disciplines in teaching Finnish and Hungarian. We explain the status of Finnish and Hungarian at University College London and in the UK, and present the principle difficulties in learning and teaching these two languages. We also introduce our courses and student profiles. With the support of examples from our own teaching, we argue that a linguistically oriented approach is well suited for less widely used and less taught languages as it enables students to draw comparative and historical parallels, question terminologies and raise their sociolinguistic and pragmatic awareness. A linguistic approach also provides students with skills for further language learning

    Approaches to verse theory in the works of Jaak PÔldmÀe

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    Approaches to verse theory in the works of Jaak PÔldmÀ

    To agree or not to agree? English adjectives in Estonian-English bilingual blogs and vlogs

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    The article focuses on the agreement (in case and number) of English adjectives used with Estonian nouns in noun phrases (Eng ADJ + EST N) in Estonian blogs and vlogs. According to the Matrix Language Frame model (MLF), one would expect English adjective stems to take on Estonian inflections, but this is not always the case. The data comes from fashion and lifestyle blogs and vlogs that have Estonian as the main language and contain English language material to various degrees. Altogether, 84 noun phrases were analysed: in 35 instances the adjective agreed with the noun and in 46 instances it did not; in 3 instances the agreement was complicated to determine. The analysis showed that English adjectives that have a sound structure similar to Estonian adjectives as a rule agree with Estonian nouns. Factors that may lead to non-agreement are stem alternation, differences in writing and pronunciation, and personal preferences. KokkuvĂ”te. Helin Kask: Ühilduda vĂ”i mitte? Inglise adjektiivid eestiinglise kakskeelsetes blogides ja vlogides. Artiklis uuritakse, kas eestiinglise kakskeelsetes blogides ja vlogides ĂŒhilduvad inglise adjektiivid eesti substan tiividega kÀÀndes ja arvus. Maatrikskeele raamistiku mudeli kohaselt eel datakse, et inglise tĂŒvele lisatakse vajalikud eesti kÀÀndelĂ”pud ja muud tunnused, siiski ei ole see alati nii. Andmed pĂ€rinevad moe-, ilu- ja elustiiliblogidest ning -vlogidest, milles pĂ”hikeel on eesti keel, kuid milles kasu tatakse ka inglise keelt. Kokku uuriti 84 nimisĂ”nafraasi (inglise ADJ + eesti SUB), neist 35 juhul ĂŒhildus inglise adjektiiv eesti substantiiviga nii arvus kui ka kÀÀndes ning 46 juhul ei ĂŒhildunud, 3 juhul ei olnud vĂ”imalik ĂŒhildumist ĂŒheselt mÀÀrata. AnalĂŒĂŒs nĂ€itas, et eesti substantiividega ĂŒhilduvad sellised ingliskeelsed adjektiivid, mis hÀÀlikulise ja silbistruktuuri poolest sarnanevad eesti muuttĂŒĂŒpide tĂŒĂŒpsĂ”nadega. MitteĂŒhildumise pĂ”hjused on astmevaheldus, erinevused kirjapildis ja hÀÀlduses, samuti informandi isiklikud eelistused
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