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1
Analyzing the impact of speaker localization errors on speech separation for automatic speech recognition
In: EUSIPCO 2020 - 28th European Signal Processing Conference ; https://hal.inria.fr/hal-02355669 ; EUSIPCO 2020 - 28th European Signal Processing Conference, Jan 2021, Amsterdam / Virtual, Netherlands. ⟨10.23919/Eusipco47968.2020.9287541⟩ ; https://eusipco2020.org/ (2021)
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2
Orofacial somatosensory inputs change the auditory categorization in perceptual adaptation training
In: 13th Annual Meeting of the Society for the Neurobiology of Language ; https://hal.archives-ouvertes.fr/hal-03460304 ; 13th Annual Meeting of the Society for the Neurobiology of Language, Oct 2021, Virtual, United States (2021)
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3
First Align, then Predict: Understanding the Cross-Lingual Ability of Multilingual BERT
In: https://hal.inria.fr/hal-03161685 ; 2021 (2021)
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4
First Align, then Predict: Understanding the Cross-Lingual Ability of Multilingual BERT
In: EACL 2021 - The 16th Conference of the European Chapter of the Association for Computational Linguistics ; https://hal.inria.fr/hal-03239087 ; EACL 2021 - The 16th Conference of the European Chapter of the Association for Computational Linguistics, Apr 2021, Kyiv / Virtual, Ukraine ; https://2021.eacl.org/ (2021)
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5
Language recognition on unknown conditions: the LORIA-Inria-MULTISPEECH system for AP20-OLR Challenge
In: Interspeech ; https://hal.archives-ouvertes.fr/hal-03228823 ; Interspeech, Aug 2021, Brno, Czech Republic (2021)
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6
Language recognition on unknown conditions: the LORIA-Inria-MULTISPEECH system for AP20-OLR Challenge
In: https://hal.archives-ouvertes.fr/hal-03228823 ; 2021 (2021)
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7
Saliva Pepsin Concentration of Laryngopharyngeal Reflux Patients Is Influenced by Meals Consumed Before the Samples
In: ISSN: 0023-852X ; Laryngoscope ; https://hal.archives-ouvertes.fr/hal-03141469 ; Laryngoscope, Wiley, 2021, 131 (2), pp.350-359. ⟨10.1002/lary.28756⟩ (2021)
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8
Frameless fictions: embodiment, affect, and unruly encounters in VR and virtual environments
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9
What do disyllabic words tell us about syllable structure, vowel quality, and stress in English?
Alwadea, Abdulrahman. - : The University of Edinburgh, 2021
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10
Paul’s designations of God in Romans
Au, Wing Yi. - : The University of Edinburgh, 2021
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11
Priorities, visions, identities, and normative approaches: a corpus-driven discourse analysis of the official discourse between China and the EU (1994-2019)
Jing, Jing. - : The University of Edinburgh, 2021
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12
Edinburgh Cognitive and Behavioural ALS Screen (ECAS) in the assessment of early onset dementia
De Icaza Valenzuela, Mónica Mariana. - : The University of Edinburgh, 2021
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13
Quo vadis? Epigraphy, language, and people in the making of Roman Italy
Nutter, Rory Henry Miles. - : The University of Edinburgh, 2021
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14
Becoming woman in the land of women: investigating the paradigm of the individual versus the collective in contemporary feminist utopianism
Ross, Rosalee. - : The University of Edinburgh, 2021
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15
Arabic dislocation
Alzayid, Ali Ahmed M. - : The University of Edinburgh, 2021
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16
Bilingualism meets autism: an investigation of executive functions profiles in English-Arabic children
Sharaan, Shereen Mohamed Elsayed Mohamed Masry. - : The University of Edinburgh, 2021
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17
RNN Language Model Estimation for Out-of-Vocabulary Words
In: Lecture Notes in Artificial Intelligence ; https://hal.archives-ouvertes.fr/hal-03054936 ; Lecture Notes in Artificial Intelligence, Springer, In press, 12598, ⟨10.1007/978-3-030-66527-2_15⟩ (2020)
Abstract: International audience ; One important issue of speech recognition systems is Out-of Vocabulary words (OOV). These words, often proper nouns or new words, are essential for documents to be transcribed correctly. Thus, they must be integrated in the language model (LM) and the lexicon of the speech recognition system. This article proposes new approaches to OOV proper noun probability estimation using Recurrent Neural Network Language Model (RNNLM). The proposed approaches are based on the notion of closest in-vocabulary (IV) words (list of brothers) to a given OOV proper noun. The probabilities of these words are used to estimate the probabilities of OOV proper nouns thanks to RNNLM. Three methods for retrieving the relevant list of brothers are studied. The main advantages of the proposed approaches are that the RNNLM is not retrained and the architecture of the RNNLM is kept intact. Experiments on real text data from the website of the Euronews channel show relative perplexity reductions of about 14% compared to baseline RNNLM.
Keyword: [INFO.INFO-HC]Computer Science [cs]/Human-Computer Interaction [cs.HC]; Neural Networks; Out-Of-Vocabulary Words; Proper Names; Speech Recognition; Vocabulary Extension
URL: https://hal.archives-ouvertes.fr/hal-03054936/file/LTC-2017-LNAI-IllinaFohr.pdf
https://doi.org/10.1007/978-3-030-66527-2_15
https://hal.archives-ouvertes.fr/hal-03054936
https://hal.archives-ouvertes.fr/hal-03054936/document
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18
Time, Place, and Manner Restrictions on Speech
Wright, R. George. - : Northern Illinois University Law Review, 2020
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19
L2 writers referencing corpora to address accuracy: a qualitative analysis of learners' lexicogrammatical error corrections
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20
(S)mothered in translation? (Re)translating the female Bildungsroman in the twentieth century in English and French
Delmas, Melina. - 2020
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