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1
Traduction de la parole dans le projet RAPMAT
In: Journées d'Études sur la Parole ; https://hal.archives-ouvertes.fr/hal-01843418 ; Journées d'Études sur la Parole, Jan 2014, Le Mans, France (2014)
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2
Speech-to-Text Development for Slovak, a Low-Resourced Language
In: International Workshop on Spoken Languages Technologies for Under-resourced languages ; https://hal.archives-ouvertes.fr/hal-01843417 ; International Workshop on Spoken Languages Technologies for Under-resourced languages, May 2014, St. Petersburg, Russia (2014)
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3
Comparing decoding strategies for subword-based keyword spotting in low-resourced languages
In: Annual Conference of the International Speech Communication Association ; https://hal.archives-ouvertes.fr/hal-01843408 ; Annual Conference of the International Speech Communication Association , ISCA, Sep 2014, Singapore, Singapore (2014)
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4
Analyzing linguistic variation in a Romanian speech corpus through ASR errors
In: Laboratory Approaches to Romance Phonology ; https://hal.archives-ouvertes.fr/hal-01843421 ; Laboratory Approaches to Romance Phonology, Laboratoire Parole et Langage (UMR 6057), Aix-en-Provence, Sep 2014, Aix-en-Provence, France (2014)
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5
Efficient Rule Scoring for Improved Grapheme-Based Lexicons
In: European Signal Processing Conference ; https://hal.archives-ouvertes.fr/hal-01843411 ; European Signal Processing Conference, Jan 2014, Lisbon, Portugal (2014)
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6
Automatic language identity tagging on word and sentence-level in multilingual text sources: a case-study on Luxembourgish
In: International Conference on Language Resources and Evaluation ; https://hal.archives-ouvertes.fr/hal-01843401 ; International Conference on Language Resources and Evaluation, May 2014, Reykjavik, Iceland (2014)
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7
Cross-Word Sub-Word Units for Low-Resource Keyword Spotting
In: International Workshop on Spoken Languages Technologies for Under-resourced languages ; https://hal.archives-ouvertes.fr/hal-01843415 ; International Workshop on Spoken Languages Technologies for Under-resourced languages, May 2014, St. Petersburg, Russia (2014)
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8
Automatic Language Identity Tagging on Word and Sentence-Level in Multilingual Text Sources: a Case-Study on Luxembourgish
In: Proceedings of the Ninth International Conference on Language Resources and Evaluation (LREC'14) ; Ninth International Conference on Language Resources and Evaluation (LREC'14) ; https://hal.archives-ouvertes.fr/hal-01134776 ; Ninth International Conference on Language Resources and Evaluation (LREC'14), European Language Resources Association (ELRA), May 2014, Reykjavik, Iceland. pp.3300-3304 ; http://lrec2014.lrec-conf.org/en/ (2014)
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9
Development of a Korean speech recognition system with little annontated data
In: International Workshop on Spoken Languages Technologies for Under-resourced languages ; https://hal.archives-ouvertes.fr/hal-01843405 ; International Workshop on Spoken Languages Technologies for Under-resourced languages, May 2014, St Petersburg, Russia (2014)
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10
Développement d'un système de reconnaissance automatique de la parole en coréen avec peu de ressources annotées
In: Journées d'Etude sur la Parole ; https://hal.archives-ouvertes.fr/hal-01843404 ; Journées d'Etude sur la Parole, Jan 2014, Le Mans, France (2014)
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11
Modélisation acoustico-phonétique de langues peu dotées : Études phonétiques et travaux de reconnaissance automatique en luxembourgois
In: Journées d'Etude sur la Parole ; https://hal.archives-ouvertes.fr/hal-01843399 ; Journées d'Etude sur la Parole, Jan 2014, Le Mans, France (2014)
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12
Exploring Pronunciation Variants for Romanian Speech-to-Text Transcription
In: International Workshop on Spoken Languages Technologies for Under-resourced languages ; https://hal.archives-ouvertes.fr/hal-01843413 ; International Workshop on Spoken Languages Technologies for Under-resourced languages, May 2014, St. Petersburg, Russia (2014)
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13
Human Annotation of ASR Error Regions: is "gravity" a Sharable Concept for Human Annotators?
In: Ninth International Conference on Language Resources and Evaluation (LREC'14) ; https://hal.archives-ouvertes.fr/hal-01134802 ; Ninth International Conference on Language Resources and Evaluation (LREC'14), May 2014, Reykjavik, Iceland. Proceedings of the Ninth International Conference on Language Resources and Evaluation (LREC'14), pp.3050-3056, 2014 ; http://lrec2014.lrec-conf.org/en/ (2014)
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14
Speech Alignment and Recognition Experiments for Luxembourgish
In: Proceedings of the 4th International Workshop on Spoken Language Technologies for Underresourced Languages ; 4th International Workshop on Spoken Language Technologies for Underresourced Languages ; https://hal.archives-ouvertes.fr/hal-01134824 ; 4th International Workshop on Spoken Language Technologies for Underresourced Languages, May 2014, Saint-Petersbourg, Russia. pp.53-60 ; http://www.mica.edu.vn/sltu2014/ (2014)
Abstract: International audience ; Luxembourgish, embedded in a multilingual context on the divide between Romance and Germanic cultures, remains one of Europe’s under-described languages. In this paper, we propose to study acoustic similarities between Luxembourgish and major contact languages (German, French, English) with the help of automatic speech alignment and recognition systems. Experiments were run using monolingual acoustic models trained on German, French and English together with (i) “multilingual” models trained on pooled speech data from these three languages, or with (ii) native Luxembourgish acoustic models from 1200 hours of untranscribed Luxembourgish audio data using unsupervised methods. We investigated whether Luxembourgish was globally better represented by one of the individual languages, by the multilingual model or by the native (unsupervised) model. While German provides globally the best acoustic match for native Luxembourgish, detailed analyses reveal language-specific preferences, in particular English and Luxembourgish models are preferred on diphthongs. The first ASR results illustrate the accuracy of the various sets of supervised monolingual and multilingual models versus unsupervised Luxembourgish acoustic models. The ASR word error rate is progressively reduced from 60 to 25% on the development data set by unsupervised training of larger context-dependent models on increasing anounts of audio data.
Keyword: [INFO.INFO-CL]Computer Science [cs]/Computation and Language [cs.CL]; [SHS.LANGUE]Humanities and Social Sciences/Linguistics; acoustic modeling; forced alignment; language similarity; languages in contact; large vocabulary speech recognition; Luxembourgish; multilingual models; under-resourced languages; unsupervised training
URL: https://hal.archives-ouvertes.fr/hal-01134824
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15
A First LVCSR System for Luxembourgish, a Low-Resourced European Language
In: Human Language Technology Challenges for Computer Science and Linguistics ; https://hal.archives-ouvertes.fr/hal-01135103 ; Zygmunt Vetulani; Joseph Mariani. Human Language Technology Challenges for Computer Science and Linguistics, 8387, Springer International Publishing, pp.479-490, 2014, 5th Language and Technology Conference, LTC 2011, Poznań, Poland, November 25--27, 2011, Revised Selected Papers, 978-3-319-08957-7. ⟨10.1007/978-3-319-08958-4_39⟩ (2014)
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16
Language Diversity: Speech Processing In A Multi-Lingual Context
In: Annual Conference of the International Speech Communication Association ; https://hal.archives-ouvertes.fr/hal-01843419 ; Annual Conference of the International Speech Communication Association , Haizhou Li, Helen Meng, Bin Ma, Eng Siong Chng, Lei Xie, Jan 2014, Singapore, Singapore (2014)
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17
Efficient Rule Scoring For Improved Grapheme-Based Lexicons ...
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