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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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| 2 |
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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Abstract:
International audience ; Since Bahdanau et al. [1] first introduced attention for neural machine translation, most sequence-to-sequence models made use of attention mechanisms [2, 3, 4]. While they produce soft-alignment matrices that could be interpreted as alignment between target and source languages, we lack metrics to quantify their quality, being unclear which approach produces the best alignments. This paper presents an empirical evaluation of 3 of the main sequence-to-sequence models for word discovery from unsegmented phoneme sequences: CNN, RNN and Transformer-based. This task consists in aligning word sequences in a source language with phoneme sequences in a target language, inferring from it word segmentation on the target side [5]. Evaluating word segmentation quality can be seen as an extrinsic evaluation of the soft-alignment matrices produced during training. Our experiments in a low-resource scenario on Mboshi and English languages (both aligned to French) show that RNNs surprisingly outperform CNNs and Transformer for this task. Our results are confirmed by an intrinsic evaluation of alignment quality through the use Average Normalized Entropy (ANE). Lastly, we improve our best word discovery model by using an alignment entropy confidence measure that accumulates ANE over all the occurrences of a given alignment pair in the collection.
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Keyword:
[INFO.INFO-CL]Computer Science [cs]/Computation and Language [cs.CL]; computational language documentation; low-resource languages; sequence-to-sequence models; soft-alignment matrices; word discovery
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URL: https://hal.archives-ouvertes.fr/hal-02193867/file/IS2019marcely-camera-ready.pdf
https://hal.archives-ouvertes.fr/hal-02193867
https://hal.archives-ouvertes.fr/hal-02193867/document
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| 3 |
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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| 4 |
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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| 5 |
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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| 6 |
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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| 7 |
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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| 8 |
ASR performance prediction on unseen broadcast programs using convolutional neurol networks
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In: IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) ; https://hal.archives-ouvertes.fr/hal-01709779 ; IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Apr 2018, Calgary, Alberta, Canada (2018)
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| 9 |
A small Griko-Italian speech translation corpus
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In: 6th international workshop on spoken language technologies for under-resourced languages(SLTU'18) ; https://hal.archives-ouvertes.fr/hal-01962528 ; 6th international workshop on spoken language technologies for under-resourced languages(SLTU'18), Aug 2018, New Delhi, India (2018)
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| 10 |
A Very Low Resource Language Speech Corpus for Computational Language Documentation Experiments
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In: Language Resources and Evaluation Conference (LREC) ; https://hal.archives-ouvertes.fr/hal-01807093 ; Language Resources and Evaluation Conference (LREC), Nicoletta Calzolari (Conference chair) and Khalid Choukri and Christopher Cieri and Thierry Declerck and Sara Goggi and Koiti Hasida and Hitoshi Isahara and Bente Maegaard and Joseph Mariani and Hélène Mazo and Asuncion Moreno and Jan Odijk and Stelios Pi, May 2018, Miyazaki, Japan (2018)
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| 11 |
Unsupervised Word Segmentation from Speech with Attention
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In: Interspeech 2018 ; https://hal.archives-ouvertes.fr/hal-01818092 ; Interspeech 2018, Sep 2018, Hyderabad, India (2018)
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| 12 |
Bayesian models for unit discovery on a very low resource language
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In: IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) ; https://hal.archives-ouvertes.fr/hal-01709589 ; IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Apr 2018, Calgary, Alberta, Canada (2018)
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| 13 |
Linguistic unit discovery from multi-modal inputs in unwritten languages: Summary of the “Speaking rosetta” JSALT 2017 workshop
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In: ICASSP 2018 - IEEE International Conference on Acoustics, Speech and Signal Processing ; https://hal.archives-ouvertes.fr/hal-01709578 ; ICASSP 2018 - IEEE International Conference on Acoustics, Speech and Signal Processing, Apr 2018, Calgary, Alberta, Canada (2018)
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| 14 |
Automatic Recognition of Affective Laughter in Spontaneous Dyadic Interactions from Audiovisual Signals
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In: International Conference on Multimodal Interaction (ICMI 2018) ; https://hal.archives-ouvertes.fr/hal-01994000 ; International Conference on Multimodal Interaction (ICMI 2018), Oct 2018, Boulder, CO, United States. pp.220-228, ⟨10.1145/3242969.3243012⟩ (2018)
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| 15 |
Token-level and sequence-level loss smoothing for RNN language models
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In: ACL - 56th Annual Meeting of the Association for Computational Linguistics ; https://hal.inria.fr/hal-01790879 ; ACL - 56th Annual Meeting of the Association for Computational Linguistics, Jul 2018, Melbourne, Australia. pp.2094-2103 ; https://aclanthology.info/papers/P18-1195/p18-1195 (2018)
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| 16 |
Adaptor Grammars for the Linguist: Word Segmentation Experiments for Very Low-Resource Languages
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In: Workshop on Computational Research in Phonetics, Phonology, and Morphology ; https://hal.archives-ouvertes.fr/hal-01910757 ; Workshop on Computational Research in Phonetics, Phonology, and Morphology, Oct 2018, Bruxelles, Belgium. pp.32 - 42, ⟨10.18653/v1/P17⟩ (2018)
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| 17 |
Parallel Corpora in Mboshi (Bantu C25, Congo-Brazzaville)
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In: 11th edition of the Language Resources and Evaluation Conference (LREC 2018) ; https://hal.archives-ouvertes.fr/hal-01710043 ; 11th edition of the Language Resources and Evaluation Conference (LREC 2018), ELRA, May 2018, Miyazaki, Japan (2018)
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| 18 |
Emergence of attention in a neural model of visually grounded speech
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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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| 19 |
Unwritten Languages Demand Attention Too! Word Discovery with Encoder-Decoder Models
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In: IEEE Automatic Speech Recognition and Understanding (ASRU) ; https://hal.archives-ouvertes.fr/hal-01592091 ; IEEE Automatic Speech Recognition and Understanding (ASRU), Dec 2017, Okinawa, Japan (2017)
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| 20 |
Unsupervised Word Discovery Using Attentional Encoder-Decoder Models
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In: WiNLP workshop, ACL 2017 ; https://hal.archives-ouvertes.fr/hal-02895851 ; WiNLP workshop, ACL 2017, Jul 2017, Vancouver, Canada (2017)
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