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All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year Sort by creator [A → Z]' creator [Z → A]' publishing year ↑ (asc)' publishing year ↓ (desc)' title [A → Z]' title [Z → A]' Simple Search Hits 1 – 4 of 4 1 Creating multi-scripts sentiment analysis lexicons for Algerian, Moroccan and Tunisian dialects Abidi, Karima; Smaïli, Kamel In: 7th International Conference on Data Mining (DTMN 2021) Computer Science Conference Proceedings in Computer Science & Information Technology (CS & IT) ; https://hal.archives-ouvertes.fr/hal-03308111 ; 7th International Conference on Data Mining (DTMN 2021) Computer Science Conference Proceedings in Computer Science & Information Technology (CS & IT), Sep 2021, Copenhagen, Denmark (2021) BASE Show details 2 A Fine-grained Multilingual Analysis Based on the Appraisal Theory: Application to Arabic and English Videos Abidi, Karima; Fohr, Dominique; Jouvet, Denis... In: ICALP: International Conference on Arabic Language Processing ; https://hal.archives-ouvertes.fr/hal-02314244 ; ICALP: International Conference on Arabic Language Processing, Oct 2019, Nancy, France. pp.49-61, ⟨10.1007/978-3-030-32959-4_4⟩ (2019) BASE Show details 3 Dynamic Extension of ASR Lexicon Using Wikipedia Data Abdullah, Badr; Illina, Irina; Fohr, Dominique In: IEEE Workshop on Spoken and Language Technology (SLT) ; https://hal.archives-ouvertes.fr/hal-01874495 ; IEEE Workshop on Spoken and Language Technology (SLT), Dec 2018, Athènes, Greece (2018) Abstract: International audience ; Despite recent progress in developing Large Vocabulary Continuous Speech Recognition Systems (LVCSR), these systems suffer from Out-Of-Vocabulary words (OOV). In many cases, the OOV words are Proper Nouns (PNs). The correct recognition of PNs is essential for broadcast news, audio indexing, etc. In this article, we address the problem of OOV PN retrieval in the framework of broadcast news LVCSR. We focused on dynamic (document dependent) extension of LVCSR lexicon. To retrieve relevant OOV PNs, we propose to use a very large multipurpose text corpus: Wikipedia. This corpus contains a huge number of PNs. These PNs are grouped in semantically similar classes using word embedding. We use a two-step approach: first, we select OOV PN pertinent classes with a multi-class Deep Neural Network (DNN). Secondly, we rank the OOVs of the selected classes. The experiments on French broadcast news show that the Bi-GRU model outperforms other studied models. Speech recognition experiments demonstrate the effectiveness of the proposed methodology. Keyword: [INFO]Computer Science [cs]; Automatic speech recognition; lexicon extension; out-of-vocabulary words; word embedding URL: https://hal.archives-ouvertes.fr/hal-01874495 https://hal.archives-ouvertes.fr/hal-01874495/file/Abdullah.pdf https://hal.archives-ouvertes.fr/hal-01874495/document BASE Hide details 4 An empirical study of the Algerian dialect of Social network Abidi, Karima; Smaïli, Kamel 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) BASE Show details

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