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MAGIC DUST FOR CROSS-LINGUAL ADAPTATION OF MONOLINGUAL WAV2VEC-2.0
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In: ICASSP 2022 ; https://hal.archives-ouvertes.fr/hal-03544515 ; ICASSP 2022, May 2022, Singapour, Singapore (2022)
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End-to-end speaker segmentation for overlap-aware resegmentation
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In: Interspeech 2021 ; https://hal-univ-lemans.archives-ouvertes.fr/hal-03257524 ; Interspeech 2021, Aug 2021, Brno, Czech Republic ; https://www.interspeech2021.org/ (2021)
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Transdisciplinary Analysis of a Corpus of French Newsreels: The ANTRACT Project
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In: ISSN: 1938-4122 ; Digital Humanities Quarterly ; https://hal.archives-ouvertes.fr/hal-03166755 ; Digital Humanities Quarterly, Alliance of Digital Humanities, 2021, Special Issue on AudioVisual Data in DH, 15 (1) ; http://digitalhumanities.org/dhq/ (2021)
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Where are we in Named Entity Recognition from Speech?
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In: 12th International Conference on Language Resources and Evaluation (LREC) ; https://hal.archives-ouvertes.fr/hal-02475026 ; 12th International Conference on Language Resources and Evaluation (LREC), May 2020, Marseille, France ; https://aclanthology.org/2020.lrec-1.556/ (2020)
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A Convolutional Deep Markov Model for Unsupervised Speech Representation Learning
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In: Interspeech 2020 ; https://hal.archives-ouvertes.fr/hal-02912029 ; Interspeech 2020, Oct 2020, Shanghai, China (2020)
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Collective memory shapes the organization of individual memories in the medial prefrontal cortex
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In: EISSN: 2397-3374 ; Nature Human Behaviour ; https://halshs.archives-ouvertes.fr/halshs-02416130 ; Nature Human Behaviour, Nature Research 2019, ⟨10.1038/s41562-019-0779-z⟩ (2019)
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Effective keyword search for low-resourced conversational speech
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In: icassp 2017 ; https://hal.archives-ouvertes.fr/hal-01744176 ; icassp 2017, IEEE, Mar 2017, La Nouvelle Orléans, United States (2017)
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Language Recognition for Dialects and Closely Related Languages
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In: Odyssey 2016 ; https://hal.archives-ouvertes.fr/hal-01744188 ; Odyssey 2016, Jun 2016, Bilbao, Spain (2016)
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Boosting bonsai trees for efficient features combination : application to speaker role identification
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In: Interspeech ; https://hal.inria.fr/hal-01025171 ; Interspeech, Sep 2014, Singapour, Singapore (2014)
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Improving recognition of proper nouns (in ASR) through generation and filtering of phonetic transcriptions
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In: ISSN: 0885-2308 ; EISSN: 1095-8363 ; Computer Speech and Language ; https://hal.archives-ouvertes.fr/hal-01433238 ; Computer Speech and Language, Elsevier, 2014, 28 (4), pp.979-996. ⟨10.1016/j.csl.2014.02.006⟩ (2014)
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Acoustics-Based Phonetic Transcription Method for Proper Nouns
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In: International Conference on Spoken Language Processing (ISCA, Interspeech 2010) ; https://hal.archives-ouvertes.fr/hal-01433899 ; International Conference on Spoken Language Processing (ISCA, Interspeech 2010), 2010, Japon (Makuhari), Unknown Region (2010)
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Iterative filtering of phonetic transcriptions of proper nouns
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In: IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2009) ; https://hal.archives-ouvertes.fr/hal-01433945 ; IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2009), 2009, Taipei, Taiwan. pp.4265--4268 (2009)
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Grapheme to phoneme conversion using an SMT system
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In: INTERNATIONAL SPEECH COMMUNICATION ASSOCIATION. ANNUAL CONFERENCE. 10TH 2009. (INTERSPEECH 2009) ; 10th Annual Conference of the International Speech Communication Association 2009 (INTERSPEECH 2009) ; https://hal.archives-ouvertes.fr/hal-01451534 ; 10th Annual Conference of the International Speech Communication Association 2009 (INTERSPEECH 2009) , Sep 2009, Brighton, United Kingdom. pp.716-719 (2009)
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Combinaison de systèmes pour la phonétisation automatique de noms propres
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In: XXVIIe Journées d'étude sur la parole (JEP 2008) ; https://hal.archives-ouvertes.fr/hal-01450912 ; XXVIIe Journées d'étude sur la parole (JEP 2008), Jun 2008, Avignon, France. pp.4 (2008)
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Combined systems for automatic phonetic transcription of proper nouns
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In: LREC 2008 Proceedings ; 6th Language Evaluation and Resources Conference (LREC 2008) ; https://hal.archives-ouvertes.fr/hal-01433960 ; 6th Language Evaluation and Resources Conference (LREC 2008), May 2008, Marrakech, Morocco. pp.1791-1795 ; http://www.lrec-conf.org/lrec2008/ (2008)
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Abstract:
International audience ; Large vocabulary automatic speech recognition (ASR) technologies perform well in known, controlled contexts. However recognition of proper nouns is commonly considered as a difficult task. Accurate phonetic transcription of a proper noun is difficult to obtain, although it can be one of the most important resources for a recognition system. In this article, we propose methods of automatic phonetic transcription applied to proper nouns. The methods are based on combinations of the rule-based phonetic transcription generator LIA PHON and an acoustic-phonetic decoding system. On the ESTER corpus, we observed that the combined systems obtain better results than our reference system (LIA PHON). The WER (Word Error Rate) decreased on segments of speech containing proper nouns, without affecting negatively the results on the rest of the corpus. On the same corpus, the Proper Noun Error Rate (PNER, which is a WER computed on proper nouns only), decreased with our new system.
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Keyword:
[INFO.INFO-CL]Computer Science [cs]/Computation and Language [cs.CL]
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URL: https://hal.archives-ouvertes.fr/hal-01433960/file/455_paper.pdf https://hal.archives-ouvertes.fr/hal-01433960 https://hal.archives-ouvertes.fr/hal-01433960/document
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