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Predicting and Critiquing Machine Virtuosity: Mawwal Accompaniment as Case Study
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In: International Computer Music Conference ; https://hal.archives-ouvertes.fr/hal-03044066 ; International Computer Music Conference, Jul 2021, Santiago, Chile (2021)
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Automatic speech recognition and machine translation of Arabic and dialectal videos ; Reconnaissance et traduction automatique de la parole de vidéos arabes et dialectales
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In: https://hal.univ-lorraine.fr/tel-03132934 ; Informatique et langage [cs.CL]. Université de Lorraine, 2020. Français. ⟨NNT : 2020LORR0157⟩ (2020)
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Summarizing videos into a target language: Methodology, architectures and evaluation
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In: ISSN: 1064-1246 ; EISSN: 1875-8967 ; Journal of Intelligent and Fuzzy Systems ; https://hal.archives-ouvertes.fr/hal-02271287 ; Journal of Intelligent and Fuzzy Systems, IOS Press, 2019, 1, pp.1-12. ⟨10.3233/JIFS-179350⟩ (2019)
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A First Summarization System of a Video in a Target Language
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In: MISSI 2018 - 11th edition of the International Conference on Multimedia and Network Information Systems ; https://hal.archives-ouvertes.fr/hal-01819720 ; MISSI 2018 - 11th edition of the International Conference on Multimedia and Network Information Systems, Sep 2018, Wrocław, Poland. pp.1-12 (2018)
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CALYOU: A Comparable Spoken Algerian Corpus Harvested from YouTube
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In: 18th Annual Conference of the International Communication Association (Interspeech) ; https://hal.archives-ouvertes.fr/hal-01531591 ; 18th Annual Conference of the International Communication Association (Interspeech), Aug 2017, Stockholm, Sweden (2017)
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About vocabulary adaptation for automatic speech recognition of video data
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In: ICNLSSP'2017 - International Conference on Natural Language, Signal and Speech Processing ; https://hal.inria.fr/hal-01649057 ; ICNLSSP'2017 - International Conference on Natural Language, Signal and Speech Processing, Dec 2017, Casablanca, Morocco. pp.1-5 (2017)
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Abstract:
International audience ; This paper discusses the adaptation of vocabularies for automatic speech recognition. The context is the transcriptions of videos in French, English and Arabic. Baseline automatic speech recognition systems have been developed using available data. However, the available text data, including the GigaWord corpora from LDC, are getting quite old with respect to recent videos that are to be transcribed. The paper presents the collection of recent textual data from internet for updating the speech recognition vocabularies and training the language models, as well as the elaboration of development data sets necessary for the vocabulary selection process. The paper also compares the coverage of the training data collected from internet, and of the GigaWord data, with finite size vocabularies made of the most frequent words. Finally, the paper presents and discusses the amount of out-of-vocabulary word occurrences, before and after update of the vocabularies, for the three languages.
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Keyword:
[INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing; Speech recognition; vocabulary; vocabulary adaptation; vocabulary selection
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URL: https://hal.inria.fr/hal-01649057 https://hal.inria.fr/hal-01649057/file/AboutTaskAdaptation-v1.2-upload.01November2017.pdf https://hal.inria.fr/hal-01649057/document
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Is statistical machine translation approach dead?
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In: ICNLSSP 2017 - International Conference on Natural Language, Signal and Speech Processing ; https://hal.inria.fr/hal-01660016 ; ICNLSSP 2017 - International Conference on Natural Language, Signal and Speech Processing, ISGA, Dec 2017, Casablanca, Morocco. pp.1-5 ; http://icnlssp.isga.ma (2017)
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A new language model based on possibility theory
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In: Springer LNCS series, Lecture Notes in Computer Science. ; https://hal.inria.fr/hal-01336535 ; Springer LNCS series, Lecture Notes in Computer Science., 2016 (2016)
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