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An Overview of Indian Spoken Language Recognition from Machine Learning Perspective
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In: ISSN: 2375-4699 ; EISSN: 2375-4702 ; ACM Transactions on Asian and Low-Resource Language Information Processing ; https://hal.inria.fr/hal-03616853 ; ACM Transactions on Asian and Low-Resource Language Information Processing, ACM, In press, ⟨10.1145/3523179⟩ (2022)
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BERT-based Semantic Model for Rescoring N-best Speech Recognition List
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In: INTERSPEECH 2021 ; https://hal.archives-ouvertes.fr/hal-03248881 ; INTERSPEECH 2021, Aug 2021, Brno, Czech Republic ; https://www.interspeech2021.org/ (2021)
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Introduction of semantic model to help speech recognition
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In: TSD 2020 - Twenty-third International Conference on Text, Speech and Dialogue ; https://hal.archives-ouvertes.fr/hal-02862245 ; TSD 2020 - Twenty-third International Conference on Text, Speech and Dialogue, Sep 2020, Brno, Czech Republic (2020)
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RNN Language Model Estimation for Out-of-Vocabulary Words
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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)
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Acoustic impacts of geometric approximation at the level of velum and epiglottis on French vowels
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In: ICPhS 2019 - International Congress of Phonetic Sciences ; https://hal.inria.fr/hal-02180566 ; ICPhS 2019 - International Congress of Phonetic Sciences, Aug 2019, Melbourne, Australia (2019)
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An integrative platform to capture the orchestration of gesture and speech
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In: GeSpIn 2019 - Gesture and Speech in Interaction ; https://hal.inria.fr/hal-02278345 ; GeSpIn 2019 - Gesture and Speech in Interaction, Sep 2019, Paderborn, Germany (2019)
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Effect of head posture on phonation of French vowels
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In: ICPhS 2019 - Proceedings of International Congress of Phonetic Sciences ; https://hal.inria.fr/hal-02180486 ; ICPhS 2019 - Proceedings of International Congress of Phonetic Sciences, Aug 2019, Melbourne, Australia (2019)
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Phoneme-to-Articulatory mapping using bidirectional gated RNN
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In: Interspeech 2018 - 19th Annual Conference of the International Speech Communication Association ; https://hal.inria.fr/hal-01862587 ; Interspeech 2018 - 19th Annual Conference of the International Speech Communication Association, Sep 2018, Hyderabad, India (2018)
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A French-Spanish Multimodal Speech Communication Corpus Incorporating Acoustic Data, Facial, Hands and Arms Gestures Information
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In: Interspeech 2018 - 19th Annual Conference of the International Speech Communication Association ; https://hal.inria.fr/hal-01862585 ; Interspeech 2018 - 19th Annual Conference of the International Speech Communication Association, Sep 2018, Hyderabad, India (2018)
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Topic segmentation in ASR transcripts using bidirectional rnns for change detection
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In: ASRU 2017 - IEEE Automatic Speech Recognition and Understanding Workshop ; https://hal.archives-ouvertes.fr/hal-01599682 ; ASRU 2017 - IEEE Automatic Speech Recognition and Understanding Workshop, Dec 2017, Okinawa, Japan (2017)
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Out-of-Vocabulary Word Probability Estimation using RNN Language Model
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In: 8th Language & Technology Conference ; https://hal.archives-ouvertes.fr/hal-01623784 ; 8th Language & Technology Conference, Nov 2017, Poznan, Poland (2017)
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Articulatory model of the epiglottis
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In: The 11th International Seminar on Speech Production ; https://hal.inria.fr/hal-01643227 ; The 11th International Seminar on Speech Production, Oct 2017, Tianjin, China (2017)
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How Diachronic Text Corpora Affect Context based Retrieval of OOV Proper Names for Audio News
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In: LREC 2016 ; https://hal.archives-ouvertes.fr/hal-01331714 ; LREC 2016, May 2016, Portoroz, Slovenia (2016)
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Improved Neural Bag-of-Words Model to Retrieve Out-of-Vocabulary Words in Speech Recognition
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In: INTERSPEECH 2016 ; https://hal.archives-ouvertes.fr/hal-01384488 ; INTERSPEECH 2016, Sep 2016, San Francisco, United States. ⟨10.21437/Interspeech.2016-1219⟩ (2016)
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Dynamic adjustment of language models for automatic speech recognition using word similarity
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In: IEEE Workshop on Spoken Language Technology (SLT 2016) ; https://hal.archives-ouvertes.fr/hal-01384365 ; IEEE Workshop on Spoken Language Technology (SLT 2016), Dec 2016, San Diego, CA, United States ; http://www.slt2016.org/ (2016)
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Document Level Semantic Context for Retrieving OOV Proper Names
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In: 2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) ; https://hal.archives-ouvertes.fr/hal-01331716 ; 2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) , Mar 2016, Shanghai, China. pp.6050-6054, ⟨10.1109/ICASSP.2016.7472839⟩ (2016)
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OOV Proper Name Retrieval using Topic and Lexical Context Model
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In: IEEE International Conference on Acoustics, Speech and Signal Processing ; https://hal.archives-ouvertes.fr/hal-01184963 ; IEEE International Conference on Acoustics, Speech and Signal Processing, 2015, Brisbane, Australia (2015)
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Continuous Word Representation using Neural Networks for Proper Name Retrieval from Diachronic Documents
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In: Interspeech 2015 ; https://hal.archives-ouvertes.fr/hal-01184951 ; Interspeech 2015, Sep 2015, Dresden, Germany (2015)
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Abstract:
International audience ; Developing high-quality transcription systems for very large vocabulary corpora is a challenging task. Proper names are usually key to understanding the information contained in a document. One approach for increasing the vocabulary coverage of a speech transcription system is to automatically retrieve new proper names from contemporary diachronic text documents. In recent years, neural networks have been successfully applied to a variety of speech recognition tasks. In this paper, we investigate whether neural networks can enhance word representation in vector space for the vocabulary extension of a speech recognition system. This is achieved by using high-quality word vector representation of words from large amounts of unstructured text data proposed by Mikolov. This model allows to take into account lexical and semantic word relationships. Proposed methodology is evaluated in the context of broadcast news transcription. Obtained recall and ASR proper name error rate is compared to that obtained using cosine-based vector space methodology. Experimental results show a good ability of the proposed model to capture semantic and lexical information
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Keyword:
[INFO.INFO-HC]Computer Science [cs]/Human-Computer Interaction [cs.HC]; neural networks; out-of-vocabulary words; proper names; speech recognition; vocabulary extension
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URL: https://hal.archives-ouvertes.fr/hal-01184951
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Neural Networks Revisited for Proper Name Retrieval from Diachronic Documents
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In: proceedings of LTC2015 ; LTC Language & Technology Conference ; https://hal.archives-ouvertes.fr/hal-01240480 ; LTC Language & Technology Conference, Nov 2015, Poznan, Poland. pp.120-124 (2015)
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Study of Entity-Topic Models for OOV Proper Name Retrieval
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In: Interspeech 2015 ; https://hal.archives-ouvertes.fr/hal-01184955 ; Interspeech 2015, Sep 2015, Dresden, Germany (2015)
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