Residual Convolutional Neural Network-Based Dysarthric Speech Recognition
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Publisher
Springer Science and Business Media LLC
Link
https://link.springer.com/content/pdf/10.1007/s13369-024-08919-5.pdf
Reference39 articles.
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2. Narendra, N.P.; Alku, P.: Automatic assessment of intelligibility in speakers with dysarthria from coded telephone speech using glottal features. Comput. Speech Lang. 65, 101117 (2020). https://doi.org/10.1016/j.csl.2020.101117
3. Sunwoo, M.K.; Hong, J.Y.; Lee, J.E.; Lee, H.S.; Lee, P.H.; Sohn, Y.H.: Depression and voice handicap in Parkinson disease. J. Neurol. Sci. 346(1–2), 112–115 (2014). https://doi.org/10.1016/j.jns.2014.08.003
4. Kumar, R.; Tripathy, M.; Kumar, N.; Anand, R.S.: Management of Parkinson’s Disease Dysarthria: Can Artificial Intelligence Provide the Solution? Ann. Indian Acad. Neurol. 25(5), 810–816 (2022). https://doi.org/10.4103/aian.aian_554_22
5. Dashtipour, K.; Tafreshi, A.; Lee, J.; Crawley, B.: Speech disorders in Parkinson’s disease: pathophysiology, medical management and surgical approaches. Neurodegener. Disease Manage. 8(5), 337–348 (2018). https://doi.org/10.2217/nmt-2018-0021
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