Voice disorder classification is an active area of research. There are many papers on the topic. The paper "Voice disorder classification using convolutional neural network based on deep transfer learning", published in May 2023, is one example (see https://www.nature.com/articles/s41598-023-34461-9). Some observations:
- The abstract indicates "The framework combines a pre-trained convolutional neural network, OpenL3, and a support vector machine (SVM) classifier."
- The OpenL3 network is easily usable in MATLAB https://www.mathworks.com/help/audio/ref/openl3.html
- The methods section indicates "This experiment is implemented based on MATLAB R2022a."
- The conclusions section indicates "Through testing on the VOICED dataset, the proposed method achieves 99.46%, 99.64%, 98.92%, and 99.64% values for the ACC, SEN, SPE, and F1 metrics, respectively. Compared with the existing works and the compared machine learning methods, the proposed method exhibits better performance."
