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Contribution d'informations syntaxiques aux capacités de généralisation compositionelle des modèles seq2seq convolutifs
In: Actes de la 28e Conférence sur le Traitement Automatique des Langues Naturelles. Volume 1 : conférence principale ; Traitement Automatique des Langues Naturelles ; https://hal.archives-ouvertes.fr/hal-03265890 ; Traitement Automatique des Langues Naturelles, 2021, Lille, France. pp.134-141 (2021)
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Catplayinginthesnow: Impact of Prior Segmentation on a Model of Visually Grounded Speech
In: Conference on Natural Language Learning (CoNLL) ; https://hal.archives-ouvertes.fr/hal-02962275 ; Conference on Natural Language Learning (CoNLL), Nov 2020, Virtual, France (2020)
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MaSS: A Large and Clean Multilingual Corpus of Sentence-aligned Spoken Utterances Extracted from the Bible
In: Proceedings of The 12th Language Resources and Evaluation Conference ; https://hal.archives-ouvertes.fr/hal-02611059 ; Proceedings of The 12th Language Resources and Evaluation Conference, May 2020, Marseille, France. pp.6486 - 6493 (2020)
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Catplayinginthesnow: Impact of Prior Segmentation on a Model of Visually Grounded Speech ...
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5
Word Recognition, Competition, and Activation in a Model of Visually Grounded Speech
In: Proceedings of the 23rd Conference on Computational Natural Language Learning (CoNLL) ; https://hal.archives-ouvertes.fr/hal-02359540 ; Proceedings of the 23rd Conference on Computational Natural Language Learning (CoNLL), Nov 2019, Hong Kong, China. pp.339-348, ⟨10.18653/v1/K19-1032⟩ (2019)
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Models of Visually Grounded Speech Signal Pay Attention to Nouns: A Bilingual Experiment on English and Japanese
In: International Conference on Acoustics, Speech and Signal Processing (ICASSP) ; https://hal.archives-ouvertes.fr/hal-02013984 ; International Conference on Acoustics, Speech and Signal Processing (ICASSP), May 2019, Brighton, United Kingdom. pp.8618-8622, ⟨10.1109/ICASSP.2019.8683069⟩ (2019)
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MaSS - Multilingual corpus of Sentence-aligned Spoken utterances ...
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MaSS - Multilingual corpus of Sentence-aligned Spoken utterances ...
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9
Word Recognition, Competition, and Activation in a Model of Visually Grounded Speech ...
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10
Models of Visually Grounded Speech Signal Pay Attention To Nouns: a Bilingual Experiment on English and Japanese ...
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11
Emergence of attention in a neural model of visually grounded speech
In: Learning Language in Humans and in Machines 2018 conference ; https://hal.archives-ouvertes.fr/hal-01970514 ; Learning Language in Humans and in Machines 2018 conference, Jul 2018, Paris, France (2018)
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12
Synthetically Spoken STAIR ...
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Synthetically Spoken STAIR ...
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SPEECH-COCO ...
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SPEECH-COCO ...
Abstract: SpeechCoco Introduction Our corpus is an extension of the MS COCO image recognition and captioning dataset. MS COCO comprises images paired with a set of five captions. Yet, it does not include any speech. Therefore, we used Voxygen's text-to-speech system to synthesise the available captions. The addition of speech as a new modality enables MSCOCO to be used for researches in the field of language acquisition, unsupervised term discovery, keyword spotting, or semantic embedding using speech and vision. Our corpus is licensed under a Creative Commons Attribution 4.0 License. Data Set This corpus contains 616,767 spoken captions from MSCOCO's val2014 and train2014 subsets (respectively 414,113 for train2014 and 202,654 for val2014). We used 8 different voices. 4 of them have a British accent (Paul, Bronwen, Judith, and Elizabeth) and the 4 others have an American accent (Phil, Bruce, Amanda, Jenny). In order to make the captions sound more natural, we used SOX tempo command, enabling us to change the speed ... : {"references": ["SPEECH-COCO: 600k Visually Grounded Spoken Captions Aligned to MSCOCO Data Set"]} ...
Keyword: audio; captions; MSCOCO; Speech; VGS; Visually Grounded Speech
URL: https://zenodo.org/record/4282267
https://dx.doi.org/10.5281/zenodo.4282267
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SPEECH-COCO: 600k Visually Grounded Spoken Captions Aligned to MSCOCO Data Set ...
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