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1
Approche multimodale par plongements de texte et de graphes pour la détection de messages abusifs
In: ISSN: 1248-9433 ; EISSN: 1965-0906 ; Revue TAL ; https://hal.archives-ouvertes.fr/hal-03527016 ; Revue TAL, ATALA (Association pour le Traitement Automatique des Langues), 2021, 62 (2), pp.13-38 ; https://www.atala.org/content/tal_62_2_-0 (2021)
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2
Team LIA/LS2N at BioCreative VII LitCovid Track: Multi-label Document Classification for COVID-19 Literature using Keyword Based Enhancement and Few-Shot Learning
In: BioCreative VII Challenge Evaluation Workshop ; https://hal.archives-ouvertes.fr/hal-03426326 ; BioCreative VII Challenge Evaluation Workshop, Nov 2021, Virtual Conference, United States (2021)
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3
Acoustic Pairing of Original and Dubbed Voices in the Context of Video Game Localization
In: Interspeech ; https://hal.archives-ouvertes.fr/hal-01572151 ; Interspeech, Aug 2017, Stockholm, Sweden. pp.2839-2843, ⟨10.21437/Interspeech.2017-1311⟩ ; http://www.isca-speech.org/archive/Interspeech_2017/abstracts/1311.html (2017)
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4
Impact Of Content Features For Automatic Online Abuse Detection
In: International Conference on Computational Linguistics and Intelligent Text Processing ; https://hal-univ-avignon.archives-ouvertes.fr/hal-01505502 ; International Conference on Computational Linguistics and Intelligent Text Processing, Apr 2017, Budapest, Hungary. pp.404-419, ⟨10.1007/978-3-319-77116-8_30⟩ (2017)
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5
Automatic Text Summarization Approaches to Speed up Topic Model Learning Process
In: ISSN: 0976-0962 ; International Journal of Computational Linguistics and Applications ; https://hal.archives-ouvertes.fr/hal-02356467 ; International Journal of Computational Linguistics and Applications, Alexander Gelbukh, 2016, 7, pp.87 - 109 (2016)
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6
Characterizing and detecting spontaneous speech: Application to speaker role recognition
In: Speech communication. - Amsterdam [u.a.] : Elsevier 56 (2014), 1-18
OLC Linguistik
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7
A Topic-Based Approach for Post-processing Correction of Automatic Translations
In: 11th International Workshop on Spoken Language Translation (IWSLT) ; https://hal.archives-ouvertes.fr/hal-02021817 ; 11th International Workshop on Spoken Language Translation (IWSLT), 2014, South Lake Tahoe, NV, United States (2014)
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8
Sumacc Project's Corpus: A Topic-based Query Extention Approach to Retrieve Multimedia Documents
In: 17th International Conference, TSD ; https://hal.archives-ouvertes.fr/hal-01319787 ; 17th International Conference, TSD, Sep 2014, Brno, Czech Republic (2014)
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9
Person name recognition in ASR outputs using continuous context models
In: IEEE International Conference on Acoustics, Speech and Signal Processing ; https://hal.archives-ouvertes.fr/hal-01314411 ; IEEE International Conference on Acoustics, Speech and Signal Processing , May 2013, Vancouver, Canada. ⟨10.1109/ICASSP.2013.6639318⟩ (2013)
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10
Person name recognition in ASR outputs using continuous context models
In: 2013 IEEE International Conference on Acoustics, Speech and Signal ; https://hal.archives-ouvertes.fr/hal-01339113 ; 2013 IEEE International Conference on Acoustics, Speech and Signal, May 2013, Vancouver, Canada (2013)
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11
Combining Acoustic Name Spotting and Continuous Context Models to improve Spoken Person Name Recognition in Speech
In: Interspeech 2013 ; https://hal.archives-ouvertes.fr/hal-02102829 ; Interspeech 2013, Aug 2013, Lyon, France (2013)
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12
Automatic transcription error recovery for Person Name Recognition
In: Interspeech 2012 ; https://hal.archives-ouvertes.fr/hal-02356295 ; Interspeech 2012, Sep 2012, Portland, United States (2012)
Abstract: International audience ; Person Name Recognition from transcriptions of TV shows spoken content is a crucial step towards multimedia document indexing. Recognizing Person Names implies the combination of three main modules: Automatic Speech Recognition, Named-Entity Recognition and Entity Linking to associate the recognized surface form to a normalized Person Name. The three modules are potentially error prone. Hence, beyond each module's intrinsic complexity, the Person Names issue suffers from the highly dynamic evolution of vocabularies and occurrence contexts that are correlated to various dimensions (such as actuality, topic of the show…). This paper focuses on the first module and proposes an approach to recover from transcription errors made on Person Names. An error correction method is applied on the textual ASR output and we show that it is all the more efficient that it is coupled with a specific error region detection system. Experiments on the French REPERE database show that Person Names transcription can be efficiently corrected while preserving the overall transcription quality and thus increasing the performance of the whole Person Name Recognition process.
Keyword: [INFO.INFO-CL]Computer Science [cs]/Computation and Language [cs.CL]; [INFO.INFO-TT]Computer Science [cs]/Document and Text Processing; person name entity recognition; transcription error detection
URL: https://hal.archives-ouvertes.fr/hal-02356295/file/i12_1007.pdf
https://hal.archives-ouvertes.fr/hal-02356295
https://hal.archives-ouvertes.fr/hal-02356295/document
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13
A Language-identification inspired method for spontaneous speech detection
In: INTERSPEECH ; https://hal.archives-ouvertes.fr/hal-01320176 ; INTERSPEECH, Sep 2010, Makuhari, Japan (2010)
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