8 results on '"Anastasiia Tsukanova"'
Search Results
2. Towards a Method of Dynamic Vocal Tract Shapes Generation by Combining Static 3D and Dynamic 2D MRI Speech Data.
- Author
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Ioannis K. Douros, Anastasiia Tsukanova, Karyna Isaieva, Pierre-André Vuissoz, and Yves Laprie
- Published
- 2019
- Full Text
- View/download PDF
3. Centerline articulatory models of the velum and epiglottis for articulatory synthesis of speech.
- Author
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Yves Laprie, Benjamin Elie, Anastasiia Tsukanova, and Pierre-André Vuissoz
- Published
- 2018
- Full Text
- View/download PDF
4. Articulatory Speech Synthesis from Static Context-Aware Articulatory Targets.
- Author
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Anastasiia Tsukanova, Benjamin Elie, and Yves Laprie
- Published
- 2017
- Full Text
- View/download PDF
5. 2D Articulatory velum modeling applied to copy synthesis of sentences containing nasal phonemes.
- Author
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Yves Laprie, Benjamin Elie, and Anastasiia Tsukanova
- Published
- 2015
6. A Multimodal Real-Time MRI Articulatory Corpus of French for Speech Research
- Author
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Arun A. Joseph, Jens Frahm, Dirk Voit, Yves Laprie, Karyna Isaieva, Freddy Odille, Ioannis Douros, Anastasiia Tsukanova, Jacques Felblinger, Pierre-André Vuissoz, Laprie, Yves, Speech Modeling for Facilitating Oral-Based Communication (MULTISPEECH), Inria Nancy - Grand Est, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Department of Natural Language Processing & Knowledge Discovery (LORIA - NLPKD), Laboratoire Lorrain de Recherche en Informatique et ses Applications (LORIA), Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)-Laboratoire Lorrain de Recherche en Informatique et ses Applications (LORIA), Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS), Imagerie Adaptative Diagnostique et Interventionnelle (IADI), Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Lorraine (UL), Biomedizinische NMR Forschungs GmbH [Göttingen], Max-Planck-Institut für Biophysikalische Chemie - Max Planck Institute for Biophysical Chemistry [Göttingen], Max-Planck-Gesellschaft-Max-Planck-Gesellschaft, and Université de Lorraine (UL)-Institut National de la Santé et de la Recherche Médicale (INSERM)
- Subjects
Larynx ,[INFO.INFO-AI] Computer Science [cs]/Artificial Intelligence [cs.AI] ,Speech production ,Epiglottis ,Computer science ,speech production ,Speech recognition ,02 engineering and technology ,speech syn- thesis ,[INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI] ,030507 speech-language pathology & audiology ,03 medical and health sciences ,Tongue ,0202 electrical engineering, electronic engineering, information engineering ,medicine ,Index Terms: speech corpus ,Spontaneous speech ,multi-modal database ,020206 networking & telecommunications ,Real-time MRI ,medicine.anatomical_structure ,Duration (music) ,French language ,real-time MRI data ,0305 other medical science ,Vocal tract ,3D MRI data - Abstract
International audience; In this work we describe the creation of ArtSpeechMRIfr: a real-time as well as static magnetic resonance imaging (rtMRI, 3D MRI) database of the vocal tract. The database contains also processed data: denoised audio, its phonetically aligned annotation, articulatory contours, and vocal tract volume information , which provides a rich resource for speech research. The database is built on data from two male speakers of French. It covers a number of phonetic contexts in the controlled part, as well as spontaneous speech, 3D MRI scans of sustained vocalic articulations, and of the dental casts of the subjects. The corpus for rtMRI consists of 79 synthetic sentences constructed from a phonetized dictionary that makes possible to shorten the duration of acquisitions while keeping a very good coverage of the phonetic contexts which exist in French. The 3D MRI includes acquisitions for 12 French vowels and 10 consonants, each of which was pronounced in several vocalic contexts. Ar-ticulatory contours (tongue, jaw, epiglottis, larynx, velum, lips) as well as 3D volumes were manually drawn for a part of the images.
- Published
- 2019
7. Centerline articulatory models of the velum and epiglottis for articulatory synthesis of speech
- Author
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Benjamin Elie, Pierre-André Vuissoz, Anastasiia Tsukanova, Yves Laprie, Laprie, Yves, Speech Modeling for Facilitating Oral-Based Communication (MULTISPEECH), Inria Nancy - Grand Est, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Department of Natural Language Processing & Knowledge Discovery (LORIA - NLPKD), Laboratoire Lorrain de Recherche en Informatique et ses Applications (LORIA), Centre National de la Recherche Scientifique (CNRS)-Université de Lorraine (UL)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-Université de Lorraine (UL)-Institut National de Recherche en Informatique et en Automatique (Inria)-Laboratoire Lorrain de Recherche en Informatique et ses Applications (LORIA), Centre National de la Recherche Scientifique (CNRS)-Université de Lorraine (UL)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-Université de Lorraine (UL), Laboratoire des signaux et systèmes (L2S), Université Paris-Sud - Paris 11 (UP11)-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS), Imagerie Adaptative Diagnostique et Interventionnelle (IADI), Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Lorraine (UL), Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)-Laboratoire Lorrain de Recherche en Informatique et ses Applications (LORIA), Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS), and Université de Lorraine (UL)-Institut National de la Santé et de la Recherche Médicale (INSERM)
- Subjects
Larynx ,Articulatory synthesis ,Epiglottis ,Deformable objects ,Computer science ,business.industry ,Articulator ,020206 networking & telecommunications ,02 engineering and technology ,01 natural sciences ,[INFO.INFO-CL]Computer Science [cs]/Computation and Language [cs.CL] ,medicine.anatomical_structure ,Index Terms-Speech ,Tongue ,[INFO.INFO-CL] Computer Science [cs]/Computation and Language [cs.CL] ,Articulatory models ,0103 physical sciences ,0202 electrical engineering, electronic engineering, information engineering ,medicine ,Computer vision ,Artificial intelligence ,business ,010301 acoustics ,Vocal tract ,MRI - Abstract
International audience; This work concerns the construction of articulatory models for synthesis of speech, and more specifically the velum and epiglottis. The direct application of principal component analysis to the contours of these articulators extracted from MRI images results in unrealistic factors due to delineation errors. The approach described in this paper relies on the application of PCA to the centerline of the articulator and a simple reconstruction algorithm to obtain the global articulator contour. The complete articulatory model was constructed from static Magnetic Resonance (MR) images because their quality is much better than that of dynamic MR images. We thus assessed the extent to which the model constructed from static images is capable of approaching the vocal tract shape in MR images recorded at 55 Hz for continuous speech. The analysis of reconstruction errors shows that it is necessary to add dynamic images to the database of static images, in particular to approach the tongue shape for the /l/ sound.
- Published
- 2018
8. Articulatory Speech Synthesis from Static Context-Aware Articulatory Targets
- Author
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Benjamin Elie, Yves Laprie, Anastasiia Tsukanova, Speech Modeling for Facilitating Oral-Based Communication (MULTISPEECH), Inria Nancy - Grand Est, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Department of Natural Language Processing & Knowledge Discovery (LORIA - NLPKD), Laboratoire Lorrain de Recherche en Informatique et ses Applications (LORIA), Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)-Laboratoire Lorrain de Recherche en Informatique et ses Applications (LORIA), Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS), Université de Lorraine (UL), Centre National de la Recherche Scientifique (CNRS), Laboratoire des signaux et systèmes (L2S), Université Paris-Sud - Paris 11 (UP11)-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS), Qiang Fang, Jianwu Dang, Pascal Perrier, Jianguo Wei, Longbiao Wang, Nan Yan, ANR-15-CE23-0024,ArtSpeech,Synthèse Articulatoire Phonétique(2015), Centre National de la Recherche Scientifique (CNRS)-Université de Lorraine (UL)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-Université de Lorraine (UL)-Institut National de Recherche en Informatique et en Automatique (Inria)-Laboratoire Lorrain de Recherche en Informatique et ses Applications (LORIA), Centre National de la Recherche Scientifique (CNRS)-Université de Lorraine (UL)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-Université de Lorraine (UL), and Tsukanova, Anastasiia
- Subjects
[INFO.INFO-AI] Computer Science [cs]/Artificial Intelligence [cs.AI] ,Articulatory synthesis ,Speech production ,Computer science ,Speech recognition ,Speech synthesis ,Context (language use) ,02 engineering and technology ,computer.software_genre ,01 natural sciences ,[INFO.INFO-CL]Computer Science [cs]/Computation and Language [cs.CL] ,[INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI] ,0103 physical sciences ,0202 electrical engineering, electronic engineering, information engineering ,coarticulation ,Articulatory gestures ,010301 acoustics ,Coarticulation ,articulatory gestures ,020206 networking & telecommunications ,[INFO.INFO-MO]Computer Science [cs]/Modeling and Simulation ,[INFO.INFO-CL] Computer Science [cs]/Computation and Language [cs.CL] ,Gestes articulatoires ,[INFO.INFO-MO] Computer Science [cs]/Modeling and Simulation ,Synthèse articulatoire ,articulatory synthesis ,Articulation (phonetics) ,computer ,Vocal tract - Abstract
Revised Selected Papers of the 11th International Seminar, ISSP 2017, Tianjin, China, October 16-19, 2017; International audience; The aim of this work is to develop an algorithm for controlling the articulators (the jaw, the tongue, the lips, the velum, the larynx and the epiglottis) to produce given speech sounds, syllables and phrases. This control has to take into account coarticulation and be flexible enough to be able to vary strategies for speech production. The data for the algorithm are 97 static MRI images capturing the articulation of French vowels and blocked consonant-vowel syllables. The results of this synthesis are evaluated visually, acoustically and perceptually, and the problems encountered are broken down by their origin: the dataset, its modeling, the algorithm for managing the vocal tract shapes, their translation to the area functions, and the acoustic simulation. We conclude that, among our test examples, the articulatory strategies for vowels and stops are most correct, followed by those of nasals and fricatives. Improving timing strategies with dynamic data is suggested as an avenue for future work.
- Published
- 2017
- Full Text
- View/download PDF
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