Consonant-Vowel Transition Models Based on Deep Learning for Objective Evaluation of Articulation.
- DOI
- 10.1109/taslp.2022.3209937
- Published
- 2023
- Container
- IEEE/ACM transactions on audio, speech, and language processing
- Publisher
- Not recorded
- Open access
- yes
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Cite this work
BibTeX
@article{allodium:10.1109/taslp.2022.3209937,
title = {Consonant-Vowel Transition Models Based on Deep Learning for Objective Evaluation of Articulation.},
author = {Mathad VC and Liss JM and Chapman K and Scherer N and Berisha V},
year = {2023},
journal = {IEEE/ACM transactions on audio, speech, and language processing},
doi = {10.1109/taslp.2022.3209937},
url = {https://doi.org/10.1109/taslp.2022.3209937}
}RIS
TY - JOUR TI - Consonant-Vowel Transition Models Based on Deep Learning for Objective Evaluation of Articulation. AU - Mathad VC AU - Liss JM AU - Chapman K AU - Scherer N AU - Berisha V PY - 2023 JO - IEEE/ACM transactions on audio, speech, and language processing DO - 10.1109/taslp.2022.3209937 UR - https://doi.org/10.1109/taslp.2022.3209937 ER -
APA
VC, M., JM, L., K, C., N, S., & V, B. (2023). Consonant-Vowel Transition Models Based on Deep Learning for Objective Evaluation of Articulation.. IEEE/ACM transactions on audio, speech, and language processing. https://doi.org/10.1109/taslp.2022.3209937
Source records
- pubmed · retrieved 2026-09-26T19:39:31.926Z