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MEDLINE as a parallel corpus: a survey to gain insight on French-, Spanish- and Portuguese-speaking authors' abstract writing practice
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In: International Conference on Language Resources and Evaluation ; https://hal.archives-ouvertes.fr/hal-03023950 ; International Conference on Language Resources and Evaluation, ELRA, May 2020, Marseille, France (2020)
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Experimenting the Automatic Recognition of Non-Conventionalized Units in Sign Language
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In: ISSN: 1999-4893 ; Algorithms ; https://hal.archives-ouvertes.fr/hal-03060271 ; Algorithms, MDPI, 2020, 13, pp.310-345. ⟨10.3390/a13120310⟩ (2020)
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The Synthesis of Complex Shape Deployments in Sign Language
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In: Proceedings of the 9th workshop on the Representation and Processing of Sign Languages ; https://hal.archives-ouvertes.fr/hal-02924673 ; Proceedings of the 9th workshop on the Representation and Processing of Sign Languages, May 2020, Marseille, France (2020)
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Use cases for a Sign Language Concordancer
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In: Proceedings of the 9th workshop on the Representation and Processing of Sign Languages ; https://hal.archives-ouvertes.fr/hal-02944491 ; Proceedings of the 9th workshop on the Representation and Processing of Sign Languages, May 2020, Marseille, France (2020)
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Elicitation and corpus of spontaneous Sign Language discourse representation diagrams
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In: Proceedings of the 9th workshop on the Representation and Processing of Sign Languages ; https://hal.archives-ouvertes.fr/hal-02924676 ; Proceedings of the 9th workshop on the Representation and Processing of Sign Languages, May 2020, Marseille, France (2020)
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RNN embeddings for identifying difficult to understand medical words
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In: ACL Workshop on Biomedical Natural Language Processing ; https://hal.archives-ouvertes.fr/hal-02371219 ; ACL Workshop on Biomedical Natural Language Processing, Aug 2019, Florence, Italy (2019)
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The NLP4NLP Corpus (II): 50 Years of Research in Speech and Language Processing
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In: ISSN: 2504-0537 ; EISSN: 2504-0537 ; Frontiers in Research Metrics and Analytics ; https://hal.archives-ouvertes.fr/hal-02413749 ; Frontiers in Research Metrics and Analytics, Frontiers Media, 2019, 3, pp.1-30 (2019)
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Challenges in Audio Processing of Terrorist-Related Data
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In: International Conference on Multimedia Modeling ; https://hal.archives-ouvertes.fr/hal-02415176 ; International Conference on Multimedia Modeling, Springer, Jan 2019, Thessaloniki, Greece (2019)
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French Levothyrox® Crisis: Retrospective Analysis of Social Media
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In: International Society of Pharmacovigilance ; https://hal.archives-ouvertes.fr/hal-02411632 ; International Society of Pharmacovigilance, Springer International Publishing, Oct 2019, Bogota, Colombia (2019)
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The NLP4NLP Corpus (I): 50 Years of Publication, Collaboration and Citation in Speech and Language Processing
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In: ISSN: 2504-0537 ; EISSN: 2504-0537 ; Frontiers in Research Metrics and Analytics ; https://hal.archives-ouvertes.fr/hal-02413751 ; Frontiers in Research Metrics and Analytics, Frontiers Media, 2019, 3, pp.1-30 (2019)
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Challenges in Audio Processing of Terrorist-Related Data
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In: International Conference on Multimedia Modeling ; https://hal.archives-ouvertes.fr/hal-02387373 ; International Conference on Multimedia Modeling, Springer, Jan 2019, Thessaloniki, Greece (2019)
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Exploiting languages proximity for part-of-speech tagging of three French regional languages
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In: ISSN: 1574-020X ; EISSN: 1574-0218 ; Language Resources and Evaluation ; https://hal.archives-ouvertes.fr/hal-02358020 ; Language Resources and Evaluation, Springer Verlag, 2019, pp.1-26 (2019)
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| 13 |
Controlling Utterance Length in NMT-based Word Segmentation with Attention
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In: International Workshop on Spoken Language Translation ; https://hal.archives-ouvertes.fr/hal-02343206 ; International Workshop on Spoken Language Translation, Nov 2019, Hong-Kong, China (2019)
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Sign Language Video Analysis For Automatic Recognition and Detection
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In: 14th IEEE International Conference on Automatic Face and Gesture Recognition ; https://hal.archives-ouvertes.fr/hal-02146366 ; 14th IEEE International Conference on Automatic Face and Gesture Recognition, May 2019, Lille, France (2019)
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| 15 |
Generic and Specialized Word Embeddings for Multi-Domain Machine Translation
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In: International Workshop on Spoken Language Translation ; https://hal.archives-ouvertes.fr/hal-02343215 ; International Workshop on Spoken Language Translation, Nov 2019, Hong-Kong, China. ⟨10.5281/zenodo.3524978⟩ ; https://zenodo.org/communities/iwslt2019/ (2019)
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Automatic recognition of Sign Language structures in RGB videos: the detection of pointing and lexical signs
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In: https://hal.archives-ouvertes.fr/hal-02146368 ; 2019 (2019)
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Optimization of a gesture representation network for Sign Language analysis
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In: https://hal.archives-ouvertes.fr/hal-02146369 ; 2019 (2019)
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| 18 |
Towards an Automatic Annotation of French Sign Language Videos: Detection of Lexical Signs
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In: CAIP 2019: Computer Analysis of Images and Patterns ; https://hal.archives-ouvertes.fr/hal-03058012 ; CAIP 2019: Computer Analysis of Images and Patterns, Sep 2019, Salerno, Italy. pp.402-412, ⟨10.1007/978-3-030-29891-3_35⟩ (2019)
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| 19 |
The perception of prosodic cues in Brazilian Portuguese statements and echo-questions: analysis by resynthesis
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In: Phonetics and Phonology in Europe Conference ; https://hal.archives-ouvertes.fr/hal-02425674 ; Phonetics and Phonology in Europe Conference, Jun 2019, Lecce, Italy (2019)
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| 20 |
Neural Baselines for Word Alignments
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In: International Workshop on Spoken Language Translation ; https://hal.archives-ouvertes.fr/hal-02343217 ; International Workshop on Spoken Language Translation, Nov 2019, Hong-Kong, China ; https://zenodo.org/communities/iwslt2019/ (2019)
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Abstract:
International audience ; Word alignments identify translational correspondences between words in a parallel sentence pair and is used, for instance, to learn bilingual dictionaries, to train statistical machine translation systems, or to perform quality estimation. In most areas of natural language processing, neural network models nowadays constitute the preferred approach, a situation that might also apply to word alignment models.In this work, we study and comprehensively evaluate neural models for unsupervised word alignment for four language pairs, contrasting several variants of neural models. We show that in most settings, neural versions of the IBM-1 and hidden Markov models vastly outperform their discrete counterparts. We also analyze typical alignment errors of the baselines that our models overcome to illustrate the benefits --- and the limitations --- of these new models for morphologically rich languages.
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Keyword:
[INFO.INFO-CL]Computer Science [cs]/Computation and Language [cs.CL]; [INFO]Computer Science [cs]; Machine Translation; Neural Machine Translation; Word Alignment
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URL: https://hal.archives-ouvertes.fr/hal-02343217/document
https://hal.archives-ouvertes.fr/hal-02343217/file/IWSLT2019_paper_23.pdf
https://hal.archives-ouvertes.fr/hal-02343217
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