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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 Page: 1 2 3 4 5...23 Hits 1 – 20 of 443 1 Ranking Semantics for Argumentation Systems With Necessities Doder, Dragan; Vesic, Srdjan; Croitoru, Madalina In: IJCAI 2020 - 29th International Joint Conference on Artificial Intelligence ; https://hal.archives-ouvertes.fr/hal-03002056 ; IJCAI 2020 - 29th International Joint Conference on Artificial Intelligence, Jan 2021, Yokohama / Virtual, Japan. pp.1912-1918, ⟨10.24963/ijcai.2020/265⟩ (2021) BASE Show details 2 A novel source-filter stochastic model for voice production Cataldo, Edson; Monteiro, L.; Soize, Christian In: ISSN: 0892-1997 ; Journal of Voice ; https://hal-upec-upem.archives-ouvertes.fr/hal-03179837 ; Journal of Voice, Elsevier, 2021, In Press, pp.1-11. ⟨10.1016/j.jvoice.2020.11.015⟩ (2021) BASE Show details 3 Investigating alignment interpretability for low-resource NMT Zanon Boito, Marcely; Villavicencio, Aline; Besacier, Laurent In: ISSN: 0922-6567 ; EISSN: 1573-0573 ; Machine Translation ; https://hal.archives-ouvertes.fr/hal-03139744 ; Machine Translation, Springer Verlag, 2021, ⟨10.1007/s10590-020-09254-w⟩ (2021) BASE Show details 4 A stochastic model of voice generation and the corresponding solution for the inverse problem using Artificial Neural Network for case with pathology in the vocal folds Cataldo, Edson; Soize, Christian In: ISSN: 1746-8094 ; Biomedical Signal Processing and Control ; https://hal-upec-upem.archives-ouvertes.fr/hal-03193501 ; Biomedical Signal Processing and Control, Elsevier, 2021, 68, pp.102623 (2021) BASE Show details 5 Impact of Encoding and Segmentation Strategies on End-to-End Simultaneous Speech Translation Nguyen, Ha; Estève, Yannick; Besacier, Laurent In: INTERSPEECH 2021 ; https://hal.archives-ouvertes.fr/hal-03372487 ; INTERSPEECH 2021, Aug 2021, Brno, Czech Republic (2021) BASE Show details 6 Alternate Endings: Improving Prosody for Incremental Neural TTS with Predicted Future Text Input Stephenson, Brooke; Hueber, Thomas; Girin, Laurent... In: Interspeech 2021 - 22nd Annual Conference of the International Speech Communication Association ; https://hal.archives-ouvertes.fr/hal-03372802 ; Interspeech 2021 - 22nd Annual Conference of the International Speech Communication Association, Aug 2021, Brno, Czech Republic. pp.3865-3869, ⟨10.21437/Interspeech.2021-275⟩ (2021) BASE Show details 7 Easy-to-use combination of POS and BERT model for domain-specific and misspelled terms Benamar, Alexandra; Bothua, Meryl; Grouin, Cyril... In: NL4IA Workshop Proceedings ; https://hal.archives-ouvertes.fr/hal-03474696 ; NL4IA Workshop Proceedings, Nov 2021, Milan, Italy (2021) BASE Show details 8 Language, Internet and Platform Competition Jeon, Doh-Shin; Jullien, Bruno; Klimenko, Mikhail In: ISSN: 0022-1996 ; Journal of International Economics ; https://hal.archives-ouvertes.fr/hal-03081660 ; Journal of International Economics, Elsevier, 2021 (2021) BASE Show details 9 Constrained control of gene-flow models Mazari, Idriss; Ruiz-Balet, Domènec; Zuazua, Enrique In: https://hal.archives-ouvertes.fr/hal-02373668 ; 2021 (2021) BASE Show details 10 English machine reading comprehension: new approaches to answering multiple-choice questions Dzendzik, Daria. - : Dublin City University. School of Computing, 2021. : Dublin City University. ADAPT, 2021 In: Dzendzik, Daria (2021) English machine reading comprehension: new approaches to answering multiple-choice questions. PhD thesis, Dublin City University. (2021) Abstract: Reading comprehension is often tested by measuring a person or system’s ability to answer questions about a given text. Machine reading comprehension datasets have proliferated in recent years, particularly for the English language. The aim of this thesis is to investigate and improve data-driven approaches to automatic reading comprehension. Firstly, I provide a full classification of question and answer types for the reading comprehension task. I also present a systematic overview of English reading comprehension datasets (over 50 datasets). I observe that the majority of questions were created using crowdsourcing and the most popular data source is Wikipedia. There is also a lack of why, when, and where questions. Additionally, I address the question “What makes a dataset difficult?” and highlight the difference between datasets created for people and datasets created for machine reading comprehension. Secondly, focusing on multiple-choice question answering, I propose a computationally light method for answer selection based on string similarities and logistic regression. At the time (December 2017), the proposed approach showed the best performance on two datasets (MovieQA and MCQA: IJCNLP 2017 Shared Task 5 Multi-choice Question Answering in Examinations) outperforming some CNN-based methods. Thirdly, I investigate methods for Boolean Reading Comprehension tasks including the use of Knowledge Graph (KG) information for answering questions. I provide an error analysis of a transformer model’s performance on the BoolQ dataset. This reveals several important issues such as unstable model behaviour and some issues with the dataset itself. Experiments with incorporating knowledge graph information into a baseline transformer model do not show a clear improvement due to a combination of the model’s ability to capture new information, inaccuracies in the knowledge graph, and imprecision in entity linking. Finally, I develop a Boolean Reading Comprehension dataset based on spontaneously user-generated questions and reviews which is extremely close to a real-life question-answering scenario. I provide a classification of question difficulty and establish a transformer-based baseline for the new proposed dataset. Keyword: Artificial intelligence; Computational linguistics; Information retrieval; Machine learning; machine reading comprehension; question answering; transformer language models URL: http://doras.dcu.ie/26534/ BASE Hide details 11 cushLEPOR uses LABSE distilled knowledge to improve correlation with human translation evaluations Han, Lifeng; Erofeev, Gleb; Gladkoff, Serge... In: Erofeev, Gleb, Sorokina, Irina, Han, Lifeng orcid:0000-0002-3221-2185 and Gladkoff, Serge (2021) cushLEPOR uses LABSE distilled knowledge to improve correlation with human translation evaluations. In: Machine Translation Summit 2021, 16-20 Aug 2021, USA (online). (In Press) (2021) BASE Show details 12 Meta-evaluation of machine translation evaluation methods Han, Lifeng In: Han, Lifeng orcid:0000-0002-3221-2185 (2021) Meta-evaluation of machine translation evaluation methods. In: Workshop on Informetric and Scientometric Research (SIG-MET), 23-24 Oct 2021, Online. (2021) BASE Show details 13 Identifying Speaker State from Multimodal Cues Yang, Zixiaofan. - 2021 BASE Show details 14 Salience Estimation and Faithful Generation: Modeling Methods for Text Summarization and Generation Kedzie, Christopher. - 2021 BASE Show details 15 Linguistic Resources Linguistic Resources for the automatic for the automatic annotation of speech annotation of speech (version 6) Bigi, Brigitte In: https://hal.archives-ouvertes.fr/hal-03468442 ; 2021 (2021) BASE Show details 16 Multiplicative Linear Logic from Logic Programs and Tilings Eng, Boris; Seiller, Thomas In: https://hal.archives-ouvertes.fr/hal-02895111 ; 2021 (2021) BASE Show details 17 A gentle introduction to Girard's Transcendental Syntax for the linear logician Eng, Boris In: https://hal.archives-ouvertes.fr/hal-02977750 ; 2021 (2021) BASE Show details 18 Stellar Resolution: Multiplicatives - for the linear logician, through examples Eng, Boris In: https://hal.archives-ouvertes.fr/hal-02977750 ; 2021 (2021) BASE Show details 19 A gentle introduction to Girard's Transcendental Syntax for the linear logician Eng, Boris In: https://hal.archives-ouvertes.fr/hal-02977750 ; 2021 (2021) BASE Show details 20 Stellar Resolution: Multiplicatives - for the linear logician, through examples Eng, Boris In: https://hal.archives-ouvertes.fr/hal-02977750 ; 2021 (2021) BASE Show details Page: 1 2 3 4 5...23

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