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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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An investigation into language model data augmentation for low-resourced STT and KWS
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In: IEEE International Conference on Acoustics, Speech, and Signal Processing ; https://hal.archives-ouvertes.fr/hal-01837171 ; IEEE International Conference on Acoustics, Speech, and Signal Processing, IEEE, Mar 2017, New Orleans, United States (2017)
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Abstract:
International audience ; This paper reports on investigations using two techniques for language model text dataaugmentation for low-resourced automatic speech recognition and keyword search. Low-resourced languages are characterized by limited training materials, which typically resultsin high out-of-vocabulary (OOV) rates and poor language model estimates. One techniquemakes use of recurrent neural networks (RNNs) using word or subword units. Word-basedRNNs keep the same system vocabulary, so they cannot reduce the OOV, whereas subwordunits can reduce the OOV but generate many false combinations. A complementarytechnique is based on automatic machine translation, which requires parallel texts and isable to add words to the vocabulary. These methods were assessed on 10 languages in thecontext of the Babel program and NIST OpenKWS evaluation. Although improvements vary across languages with both methods, small gains were generally observed in terms of word error rate reduction and improved keyword search performance.
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Keyword:
[INFO.INFO-CL]Computer Science [cs]/Computation and Language [cs.CL]; [INFO]Computer Science [cs]; keyword search; low resourced languages; multilingual; speech recognition
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URL: https://hal.archives-ouvertes.fr/hal-01837171
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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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Language Model Data Augmentation for Keyword Spotting
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In: Annual Conference of the International Speech Communication Association ; https://hal.archives-ouvertes.fr/hal-01837186 ; Annual Conference of the International Speech Communication Association , Jan 2016, San Francisco, United States (2016)
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Investigating techniques for low resource conversational speech recognition
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In: 2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) ; 41st IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2016) ; https://hal-univ-lemans.archives-ouvertes.fr/hal-01515254 ; 41st IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2016), Mar 2016, Shangai, China. pp.5975-5979, ⟨10.1109/ICASSP.2016.7472824⟩ ; www.icassp2016.org (2016)
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Traduction de la parole dans le projet RAPMAT
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In: Journées d'Études sur la Parole ; https://hal.archives-ouvertes.fr/hal-01843418 ; Journées d'Études sur la Parole, Jan 2014, Le Mans, France (2014)
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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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Development of a Korean speech recognition system with little annontated data
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In: International Workshop on Spoken Languages Technologies for Under-resourced languages ; https://hal.archives-ouvertes.fr/hal-01843405 ; International Workshop on Spoken Languages Technologies for Under-resourced languages, May 2014, St Petersburg, Russia (2014)
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Développement d'un système de reconnaissance automatique de la parole en coréen avec peu de ressources annotées
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In: Journées d'Etude sur la Parole ; https://hal.archives-ouvertes.fr/hal-01843404 ; Journées d'Etude sur la Parole, Jan 2014, Le Mans, France (2014)
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