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Open-Source Manually Annotated Vocal Tract Database for Automatic Segmentation from 3D MRI Using Deep Learning: Benchmarking 2D and 3D Convolutional and Transformer Networks

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Resource type
Journal Article
Authors/contributors
Title
Open-Source Manually Annotated Vocal Tract Database for Automatic Segmentation from 3D MRI Using Deep Learning: Benchmarking 2D and 3D Convolutional and Transformer Networks
Publication
Journal of Voice
Date
3/2025
Pages
S089219972500075X
Journal Abbr
Journal of Voice
DOI
10.1016/j.jvoice.2025.02.026
Citation Key
erattakulangara.etal_2025
URL
https://linkinghub.elsevier.com/retrieve/pii/S089219972500075X
Accessed
16/05/2025, 16:27
ISSN
08921997
Short Title
Open-Source Manually Annotated Vocal Tract Database for Automatic Segmentation from 3D MRI Using Deep Learning
Language
en
Library Catalog
DOI.org (Crossref)
Citation
Erattakulangara, S., Kelat, K., Burnham, K., Balbi, R., Gerard, S. E., Meyer, D., & Lingala, S. G. (2025). Open-Source Manually Annotated Vocal Tract Database for Automatic Segmentation from 3D MRI Using Deep Learning: Benchmarking 2D and 3D Convolutional and Transformer Networks. Journal of Voice, S089219972500075X. https://doi.org/10.1016/j.jvoice.2025.02.026
Speech Production Data
Link to this record
https://catalogue.yorvoice.york.ac.uk/catalogue/UNZBTKSB
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