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Computational models of disfluencies : fillers and discourse markers in spoken language understanding ; Modèles computationnels des disfluences dans le traitement de la parole
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In: https://tel.archives-ouvertes.fr/tel-03653211 ; Computer science. Institut Polytechnique de Paris, 2022. English. ⟨NNT : 2022IPPAT001⟩ (2022)
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Xie, X., Liu, L., & Jaeger, T. F. (2021-JEP:G). Cross-talker generalization in the perception of non-nativespeech: a large-scale replication ...
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Improved Spoken Language Representation for Intent Understanding in a Task-Oriented Dialogue System
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In: Sensors; Volume 22; Issue 4; Pages: 1509 (2022)
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Where are we in semantic concept extraction for Spoken Language Understanding? ⋆
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In: SPECOM 2021 23rd International Conference on Speech and Computer ; https://hal.archives-ouvertes.fr/hal-03372494 ; SPECOM 2021 23rd International Conference on Speech and Computer, Sep 2021, Saint Petersburg, Russia (2021)
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Phonetic detail is used to predict a word’s morphological composition ...
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Learning speech embeddings for speaker adaptation and speech understanding
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Modeling phones, keywords, topics and intents in spoken languages
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What is best for Spoken Language Understanding: Small but Task-dependant Embeddings or Huge but Out-of-domain Embeddings?
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In: IEEE International Conference on Acoustics, Speech, and Signal Processing ; https://hal.archives-ouvertes.fr/hal-02503694 ; IEEE International Conference on Acoustics, Speech, and Signal Processing, May 2020, Barcelone, Spain (2020)
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The importance of fillers for text representations of speech transcripts
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In: Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP) ; https://hal.archives-ouvertes.fr/hal-03134854 ; Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP), Association for Computational Linguistics, Nov 2020, Online, Dominican Republic. pp.7985-7993, ⟨10.18653/v1/2020.emnlp-main.641⟩ (2020)
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SLURP: A Spoken Language Understanding Resource Package ...
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SLURP: A Spoken Language Understanding Resource Package ...
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Towards Programming in Natural Language: Learning New Functions from Spoken Utterances ...
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Towards Programming in Natural Language: Learning New Functions from Spoken Utterances
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In: International journal of semantic computing, 14 (2), 249–272 ; ISSN: 1793-351X, 1793-7108 (2020)
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Neural Models for Integrating Prosody in Spoken Language Understanding
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Advances in deep learning methods for speech recognition and understanding
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Adapting a FrameNet Semantic Parser for Spoken Language Understanding Using Adversarial Learning
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In: Interspeech 2019 ; https://hal.archives-ouvertes.fr/hal-02298417 ; Interspeech 2019, Sep 2019, Graz, Austria. pp.799-803, ⟨10.21437/Interspeech.2019-2732⟩ (2019)
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Seq2Biseq: Bidirectional Output-wise Recurrent Neural Networks for Sequence Modelling
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In: CICLing 2019 - 20th International Conference on Computational Linguistics and Intelligent Text Processing ; https://hal.inria.fr/hal-02085093 ; CICLing 2019 - 20th International Conference on Computational Linguistics and Intelligent Text Processing, Apr 2019, La Rochelle, France (2019)
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Intelligibility and Listening Effort of Spanish Oesophageal Speech
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In: Applied Sciences ; Volume 9 ; Issue 16 (2019)
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Data-Driven Language Understanding for Spoken Dialogue Systems ...
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