Research on automatic assessment of the severity of unilateral vocal cord paralysis based on Mel-spectrogram and convolutional neural networks
This study demonstrates the potential of deep learning-based non-invasive voice analysis for precise grading of UVCP severity. The proposed method offers a promising clinical tool to assist physicians in disease assessment and personalized treatment planning.
Authors
- Yutang Wang (ORCID: https://orcid.org/0000-0002-6264-6443)
- Zhong‐Lin Lu (ORCID: https://orcid.org/0000-0002-7295-727X)
- Jianbo Yu (ORCID: https://orcid.org/0000-0003-3204-2486)
- Shuailing Ma (ORCID: https://orcid.org/0000-0002-0751-0463)
- Chen Zhao (ORCID: https://orcid.org/0000-0003-3844-3192)
- Fan Zhang (ORCID: https://orcid.org/0000-0002-1792-5195)
- Peijie He
- Weizhi Liao (ORCID: https://orcid.org/0000-0003-2249-7401)
- Yi Zhang (ORCID: https://orcid.org/0000-0001-6223-4724)
Institutions
- University of Shanghai for Science and Technology (CN)
- Fudan University (CN)
Publication Details
- Journal
- BioMedical Engineering OnLine
- Published
- 2025-06-21
- DOI
- https://doi.org/10.1186/s12938-025-01401-9
- Citations
- 4
- Primary Topic
- Voice and Speech Disorders
- Type
- article
- Field-Weighted Citation Impact
- 4.66
Funders
- Shanghai Municipal Health Commission
- National Natural Science Foundation of China