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Controlling Utterance Length in NMT-based Word Segmentation with Attention
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In: International Workshop on Spoken Language Translation ; https://hal.archives-ouvertes.fr/hal-02343206 ; International Workshop on Spoken Language Translation, Nov 2019, Hong-Kong, China (2019)
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Empirical Evaluation of Sequence-to-Sequence Models for Word Discovery in Low-resource Settings
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In: Interspeech 2019 ; https://hal.archives-ouvertes.fr/hal-02193867 ; Interspeech 2019, Sep 2019, Graz, Austria (2019)
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Word Recognition, Competition, and Activation in a Model of Visually Grounded Speech
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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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The Zero Resource Speech Challenge 2019: TTS without T
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In: Interspeech 2019 - 20th Annual Conference of the International Speech Communication Association ; https://hal.archives-ouvertes.fr/hal-02274112 ; Interspeech 2019 - 20th Annual Conference of the International Speech Communication Association, Sep 2019, Graz, Austria (2019)
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Models of Visually Grounded Speech Signal Pay Attention to Nouns: A Bilingual Experiment on English and Japanese
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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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A neural approach for inducing multilingual resources and natural language processing tools for low-resource languages
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In: ISSN: 1351-3249 ; EISSN: 1469-8110 ; Natural Language Engineering ; https://hal.archives-ouvertes.fr/hal-01976297 ; Natural Language Engineering, Cambridge University Press (CUP), 2019, 25 (01), pp.43-67. ⟨10.1017/S1351324918000293⟩ (2019)
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How Does Language Influence Documentation Workflow? Unsupervised Word Discovery Using Translations in Multiple Languages
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In: Journées Scientifiques du Groupement de Recherche: Linguistique Informatique, Formelle et de Terrain (LIFT). ; https://hal.archives-ouvertes.fr/hal-02895895 ; Journées Scientifiques du Groupement de Recherche: Linguistique Informatique, Formelle et de Terrain (LIFT)., Nov 2019, Orléans, France (2019)
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Controlling Utterance Length in NMT-based Word Segmentation with Attention ...
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Controlling Utterance Length in NMT-based Word Segmentation with Attention ...
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Controlling Utterance Length in NMT-based Word Segmentation with Attention ...
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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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How Does Language Influence Documentation Workflow? Unsupervised Word Discovery Using Translations in Multiple Languages ...
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Word Recognition, Competition, and Activation in a Model of Visually Grounded Speech ...
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Abstract:
In this paper, we study how word-like units are represented and activated in a recurrent neural model of visually grounded speech. The model used in our experiments is trained to project an image and its spoken description in a common representation space. We show that a recurrent model trained on spoken sentences implicitly segments its input into word-like units and reliably maps them to their correct visual referents. We introduce a methodology originating from linguistics to analyse the representation learned by neural networks -- the gating paradigm -- and show that the correct representation of a word is only activated if the network has access to first phoneme of the target word, suggesting that the network does not rely on a global acoustic pattern. Furthermore, we find out that not all speech frames (MFCC vectors in our case) play an equal role in the final encoded representation of a given word, but that some frames have a crucial effect on it. Finally, we suggest that word representation could be ... : Accepted at CoNLL2019 ...
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Keyword:
Computation and Language cs.CL; FOS Computer and information sciences; Machine Learning cs.LG
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URL: https://dx.doi.org/10.48550/arxiv.1909.08491 https://arxiv.org/abs/1909.08491
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Models of Visually Grounded Speech Signal Pay Attention To Nouns: a Bilingual Experiment on English and Japanese ...
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