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Investigating data sharing in speech recognition for an underresourced language: the case of algerian dialect
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In: 7th International Conference on Natural Language Processing - NATP 2021 ; https://hal.archives-ouvertes.fr/hal-03137048 ; 7th International Conference on Natural Language Processing - NATP 2021, Mar 2021, Vienna, Austria (2021)
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REFLEXIÓN SOBRE EL USO DE LA LENGUA ARGELINA: ANÁLISIS DE LA SITUACIÓN SOCIOLINGÜÍSTICA EN TIEMPOS DE CORONAVIRUS
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In: Tonos Digital; NÚMERO 40- ENERO 2021 (2021)
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An Algerian Corpus and an Annotation Platform for Opinion and Emotion Analysis
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In: Proceedings of the 12th Language Resources and Evaluation Conference ; 12th Language Resources and Evaluation Conference, LREC 2020 ; https://hal.archives-ouvertes.fr/hal-03102495 ; 12th Language Resources and Evaluation Conference, LREC 2020, May 2020, Marseille, France. pp.1202-1210 ; https://www.aclweb.org/anthology/2020.lrec-1.151/ (2020)
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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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Abstract:
This research has been developed in the framework of the project AMIS (Access to Multilingual Information and opinionS). AMIS is an European project which aims to help people to understand the main idea of a video in a foreign language by generating an automatic summary of it. In this thesis, we focus on the automatic recognition and translation of the speech of Arabic and dialectal videos. The statistical approaches proposed in the literature for automatic speech recognition are language independent and they are applicable to modern standard Arabic. However, this language presents some characteristics that we need to take into consideration in order to boost the performance of the speech recognition system. Among these characteristics we can mention the absence of short vowels in the text, which makes their training by the acoustic model difficult. We proposed several approaches to acoustic and/or language modeling in order to better recognize the Arabic speech. In the Arab world, modern standard Arabic is not the mother tongue, that is why daily conversations are carried out with dialect, an Arabic inspired from modern standard Arabic, but not only. We worked on the adaptation of the speech recognition system developed for the modern standard Arabic to the Algerian dialect, which is one of the most difficult variants of the Arabic language to recognize by automatic speech recognition systems. This is mainly due to the borrowed words from other languages, the code-switching and the lack of resources. Our approach to overcome all these problems is to take advantage from oral and textual data of other languages that have an impact on the dialect in order to train the required models for dialect speech recognition. The resulting text from Arabic speech recognition system was then used for machine translation. As a starting point, we conducted a comparative study between the phrase based approach and the neural approach used in machine translation. Then, we adapted these two approaches to translate the code-switched text. Our study focused on the mix of Arabic and English in a parallel corpus extracted from official documents of the United Nations. In order to prevent the error propagation in the pipeline system, we worked on the adaptation of the vocabulary of the automatic speech recognition system and on the proposition of a new model that directly transforms a speech signal in language A into a sequence of words in another language B. ; Les travaux de recherche ont été développés dans le cadre du projet AMIS (Access to Multilingual Information and opinionS) dont l'objectif principal est de développer un système d’aide à la compréhension de vidéos dans des langues étrangères en générant un résumé automatique de ces dernières dans une langue compréhensible par l'utilisateur. Dans le cadre de cette thèse, nous nous sommes concentrés sur la reconnaissance et la traduction automatique de la parole de vidéos arabes et dialectales. Les approches statistiques proposées dans la littérature pour la reconnaissance automatique de la parole (RAP) sont indépendantes de la langue et elles sont applicables à l'arabe standard. Cependant, cette dernière présente quelques caractéristiques que nous devons prendre en considération afin de booster les performances du système de RAP. Parmi ces caractéristiques on peut citer l'absence de l'indication des voyelles dans le texte ce qui rend difficile leur apprentissage par le modèle acoustique. Nous avons proposé plusieurs approches de modélisation acoustique et/ou de langage afin de mieux reconnaître la parole arabe. L'arabe standard n'est pas la langue maternelle, c'est pourquoi dans les conversations quotidiennes, on utilise le dialecte, un arabe inspiré de l'arabe standard, mais pas seulement. Nous avons travaillé sur l'adaptation du système développé pour l'arabe standard au dialecte algérien qui est l'une des variantes de la langue arabe les plus difficiles à reconnaître par les systèmes de RAP. Cela est dû aux mots empruntés d'autres langues, au code-switching et au manque de ressources. Notre proposition pour remédier à ces problèmes est de tirer profit des données orales et textuelles d'autres langues impactant le dialecte. Le texte résultant de la RAP arabe a été utilisé pour la traduction automatique (TA). Nous avons réalisé dans un premier temps une étude comparative entre l'approche statistique à base de segments et l'approche neuronale utilisées dans le cadre de la TA. Ensuite, nous nous sommes intéressés à l’adaptation de ces deux approches pour traduire le texte code-switché. Notre étude portait sur le mélange de l'arabe et de l'anglais dans des documents officiels des nations unies. Pour pallier les différents problèmes dus à la propagation des erreurs dans le système séquentiel, nous avons travaillé sur l'adaptation du vocabulaire du système de RAP et sur la proposition d'une nouvelle modélisation permettant la traduction directe de la parole.
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Keyword:
[INFO.INFO-CL]Computer Science [cs]/Computation and Language [cs.CL]; Algerian dialect; Arabe standard; Automatic speech recognition; Code-switching; Dialecte algérien; Machine translation; Modern standard Arabic; Reconnaissance automatique de la parole; Traduction automatique
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URL: https://hal.univ-lorraine.fr/tel-03132934/file/DDOC_T_2020_0157_MENACER.pdf
https://hal.univ-lorraine.fr/tel-03132934
https://hal.univ-lorraine.fr/tel-03132934/document
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The SMarT Classifier for Arabic Fine-Grained Dialect Identification
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In: MADAR Shared Task: Arabic Fine-Grained Dialect Identification Dialect identification campaign ; The Fourth Arabic Natural Language Processing Workshop co-located with ACL ; https://hal.archives-ouvertes.fr/hal-02166384 ; The Fourth Arabic Natural Language Processing Workshop co-located with ACL, Aug 2019, Florence, Italy (2019)
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Approche Hybride pour la translitération de l’arabizi algérien : une étude préliminaire
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In: 25e conférence sur le Traitement Automatique des Langues Naturelles (TALN) ; https://hal.archives-ouvertes.fr/hal-01837234 ; 25e conférence sur le Traitement Automatique des Langues Naturelles (TALN), May 2018, Rennes, France (2018)
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An Automatic Learning of an Algerian Dialect Lexicon by using Multilingual Word Embeddings
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In: Proceedings of 11th edition of the Language Resources and Evaluation Conference, ; 11th edition of the Language Resources and Evaluation Conference, LREC 2018 ; https://hal.archives-ouvertes.fr/hal-01718110 ; 11th edition of the Language Resources and Evaluation Conference, LREC 2018, May 2018, Miyazaki, Japan (2018)
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Statistical Machine Translation: Application to low resourced languages ; Traduction Automatique Fondée sur des Méthodes Statistiques : Application aux Langues peu Dotées en Ressources
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In: https://hal.inria.fr/tel-03186940 ; Computation and Language [cs.CL]. École Supérieure d’Informatique, 2018. English (2018)
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SentiALG: Automated Corpus Annotation for Algerian Sentiment Analysis
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Comparison between Neural and Statistical translation after transliteration of Algerian Arabic Dialect
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In: WiNLP: Women & Underrepresented Minorities in Natural Language Processing (co-located withACL 2017) ; https://hal.archives-ouvertes.fr/hal-01570298 ; WiNLP: Women & Underrepresented Minorities in Natural Language Processing (co-located withACL 2017), Jul 2017, Vancouver, Canada ; http://www.winlp.org/winlp-workshop (2017)
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Maghrebi Arabic dialect processing: an overview
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In: ICNLSSP 2017 - International Conference on Natural Language, Signal and Speech Processing ; https://hal.inria.fr/hal-01660001 ; ICNLSSP 2017 - International Conference on Natural Language, Signal and Speech Processing, ISGA, Dec 2017, Casablanca, Morocco (2017)
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An empirical study of the Algerian dialect of Social network
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In: ICNLSSP 2017 - International Conference on Natural Language, Signal and Speech Processing ; https://hal.inria.fr/hal-01659997 ; ICNLSSP 2017 - International Conference on Natural Language, Signal and Speech Processing, Dec 2017, Casablanca, Morocco ; http://icnlssp.isga.ma (2017)
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Development of the Arabic Loria Automatic Speech Recognition system (ALASR) and its evaluation for Algerian dialect
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In: ACLing 2017 - 3rd International Conference on Arabic Computational Linguistics ; https://hal.archives-ouvertes.fr/hal-01583842 ; ACLing 2017 - 3rd International Conference on Arabic Computational Linguistics, Nov 2017, Dubai, United Arab Emirates. pp.1-8 (2017)
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From existential to indefinite determiner ; From existential to indefinite determiner: Kaš in Algerian Arabic
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In: Arabic Varieties: Far and Wide. Proceedings of the 11th International Conference of AIDA – Bucharest, 2015 ; https://halshs.archives-ouvertes.fr/halshs-01277582 ; Grigore, George; Bițună, Gabriel. Arabic Varieties: Far and Wide. Proceedings of the 11th International Conference of AIDA – Bucharest, 2015, Editura Universității din București, pp.505-513, 2016, 978-606-16-0709-9 (2016)
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An Algerian dialect: Study and Resources
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In: ISSN: 2158-107X ; EISSN: 2156-5570 ; International journal of advanced computer science and applications (IJACSA) ; https://hal.archives-ouvertes.fr/hal-01297415 ; International journal of advanced computer science and applications (IJACSA), The Science and Information Organization, 2016, 7 (3), pp.384-396. ⟨10.14569/IJACSA.2016.070353⟩ (2016)
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From existential to indefinite determiner ; From existential to indefinite determiner: Kaš in Algerian Arabic
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In: Arabic Varieties: Far and Wide. Proceedings of the 11th International Conference of AIDA – Bucharest, 2015 ; https://halshs.archives-ouvertes.fr/halshs-01277582 ; Grigore, George; Bițună, Gabriel. Arabic Varieties: Far and Wide. Proceedings of the 11th International Conference of AIDA – Bucharest, 2015, Editura Universității din București, pp.505-513, 2016, 978-606-16-0709-9 (2016)
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From existential to indefinite determiner ; From existential to indefinite determiner: kaš in Algerian Arabic
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In: 11th Conference of AIDA ; https://hal.archives-ouvertes.fr/hal-01482562 ; 11th Conference of AIDA, Association Internationale de Dialectologie Arabe (AIDA), May 2015, Bucharest, Romania ; http://aidabucharest2015.lls.unibuc.ro/ (2015)
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From existential to indefinite determiner ; From existential to indefinite determiner: kaš in Algerian Arabic
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In: 11th Conference of AIDA ; https://hal.archives-ouvertes.fr/hal-01482562 ; 11th Conference of AIDA, Association Internationale de Dialectologie Arabe (AIDA), May 2015, Bucharest, Romania ; http://aidabucharest2015.lls.unibuc.ro/ (2015)
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Building Resources for Algerian Arabic Dialects
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In: 15th Annual Conference of the International Communication Association Interspeech ; https://hal.inria.fr/hal-01066989 ; 15th Annual Conference of the International Communication Association Interspeech, ISCA, Sep 2014, Singapour, Singapore (2014)
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A Study of a Non-Resourced Language: The Case of one of the Algerian Dialects
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In: Proceedings of The third International Workshop on Spoken Languages Technologies for Under-resourced Languages ; The third International Workshop on Spoken Languages Technologies for Under-resourced Languages - SLTU'12 ; https://hal.archives-ouvertes.fr/hal-00727042 ; The third International Workshop on Spoken Languages Technologies for Under-resourced Languages - SLTU'12, May 2012, Cape-town, South Africa. pp.1-7 (2012)
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