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Automatic generation of the complete vocal tract shape from the sequence of phonemes to be articulated
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In: ISSN: 0167-6393 ; EISSN: 1872-7182 ; Speech Communication ; https://hal.univ-lorraine.fr/hal-03650212 ; Speech Communication, Elsevier : North-Holland, 2022, ⟨10.1016/j.specom.2022.04.004⟩ (2022)
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MRI Vocal Tract Sagittal Slices Estimation during Speech Production of CV
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In: EUSIPCO 2020 - 28th European Signal Processing Conference ; https://hal.inria.fr/hal-03090824 ; EUSIPCO 2020 - 28th European Signal Processing Conference, Jan 2021, Amsterdam / Virtual, Netherlands ; https://eusipco2020.org/ (2021)
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Abstract:
International audience ; In this paper we propose an algorithm for estimating vocal tract para sagittal slices in order to have a better overview of the behaviour of the articulators during speech production. The first step is to align the consonant-vowel (CV) data of the sagittal plains between them for the train speaker. Sets of transformations that connect the midsagittal frames with the neighbouring ones is acquired for the train speaker. Another set of transformations is calculated which transforms the midsagittal frames of the train speaker to the corresponding midsagittal frames of the test speaker and is used to adapt to the test speaker domain the previously computed sets of transformations. The newly adapted transformations are applied to the midsagittal frames of the test speaker in order to estimate the neighbouring sagittal frames. Several mono speaker models are combined to produce the final frame estimation. To evaluate the results, image cross-correlation between the original and the estimated frames was used. Results show good agreement between the original and the estimated frames.
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Keyword:
[INFO.INFO-CL]Computer Science [cs]/Computation and Language [cs.CL]; [INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing; Image transformation; RtMRI data; speech resources enrichment; vocal tract
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URL: https://hal.inria.fr/hal-03090824/document
https://hal.inria.fr/hal-03090824
https://hal.inria.fr/hal-03090824/file/3D_EUSIPCO_2020.pdf
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Multimodal dataset of real-time 2D and static 3D MRI of healthy French speakers
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In: ISSN: 2052-4463 ; EISSN: 2052-4463 ; Scientific Data ; https://hal.archives-ouvertes.fr/hal-03507532 ; Scientific Data , Nature Publishing Group, 2021, 8 (1), pp.258. ⟨10.1038/s41597-021-01041-3⟩ (2021)
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Towards the prediction of the vocal tract shape from the sequence of phonemes to be articulated
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In: iNTERSPEECH 2021 ; https://hal.inria.fr/hal-03360113 ; iNTERSPEECH 2021, Aug 2021, Brno, Czech Republic (2021)
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