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DNN-Based Parametric Speech Synthesis Enhanced With Articulatory Information
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In: ISSP 2020 - 12th International Seminar on Speech Production ; https://hal.inria.fr/hal-03090869 ; ISSP 2020 - 12th International Seminar on Speech Production, Dec 2020, Providence / Virtual, United States ; https://issp2020.yale.edu/ (2020)
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Articulatory speech synthesis ; Synthèse articulatoire de la parole
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In: https://hal.archives-ouvertes.fr/tel-02433528 ; Computation and Language [cs.CL]. Université de Lorraine, 2019. English. ⟨NNT : 2019LORR0166⟩ (2019)
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A Multimodal Real-Time MRI Articulatory Corpus of French for Speech Research
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In: INTERSPEECH 2019 - 20th Annual Conference of the International Speech Communication Association ; https://hal.inria.fr/hal-02167756 ; INTERSPEECH 2019 - 20th Annual Conference of the International Speech Communication Association, Sep 2019, Graz, Austria (2019)
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Can static vocal tract positions represent articulatory targets in continuous speech? Matching static MRI captures against real-time MRI for the French language
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In: ICPhS 2019 - International Congress of Phonetic Sciences ; https://hal.inria.fr/hal-02181314 ; ICPhS 2019 - International Congress of Phonetic Sciences, Aug 2019, Melbourne, Australia (2019)
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Abstract:
International audience ; This paper uses mediosagittal slices of a static magnetic resonance imaging (MRI) dataset capturing the blocked articulation of vowels and of consonants that anticipate /a, i, u, y/ and a variety of other vowels to study the presence and distinctness of these deliberately taken articu-latory targets in real-time MRI recordings. The study investigates whether such articulatory targets are actually attained in fluent speech, how marked they are, and what factors influence the degree of similarity between a given articulatory target and the actual vocal tract shape. To quantify the similarity, we use structural similarity, Wasserstein distance, and SIFT measure. We analyze the amplitude and timing of the observed similarity peaks across different phonetic classes and speech types (spon-taneous versus not). We show that although real-time speech involves shapes quite similar to the static data, there is a great intra-and inter-speaker variability.
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Keyword:
[INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]; [INFO]Computer Science [cs]; articulatory targets; coarticulation; speech production
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URL: https://hal.inria.fr/hal-02181314
https://hal.inria.fr/hal-02181314/file/art_targ.pdf
https://hal.inria.fr/hal-02181314/document
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Articulatory Speech Synthesis from Static Context-Aware Articulatory Targets
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In: ISSP 2017 - 11th International Seminar on Speech Production ; https://hal.archives-ouvertes.fr/hal-01643487 ; ISSP 2017 - 11th International Seminar on Speech Production, Oct 2017, Tianjin, China (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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| 7 |
2D Articulatory Velum Modeling Applied to Copy Synthesis of Sentences Containing Nasal Phonemes
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In: International Congress of Phonetic Sciences ; https://hal.inria.fr/hal-01188738 ; International Congress of Phonetic Sciences, Aug 2015, Glasgow, United Kingdom (2015)
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