| This dataset contains 2000 samples for dysarthric males, dysarthric females, non-dysarthric males, and non-dysarthric females. | |
| Originally TORGO database contains 18GB of data, to download and for more information on data, please refer to the following link, | |
| http://www.cs.toronto.edu/~complingweb/data/TORGO/torgo.html | |
| This database should be used only for academic purposes. | |
| Database / Licence Reference: | |
| Rudzicz, F., Namasivayam, A.K., Wolff, T. (2012) The TORGO database of acoustic and articulatory speech from speakers with dysarthria. Language Resources and Evaluation, 46(4), pages 523--541. | |
| Data Information: | |
| It contains four folders with descriptions below, | |
| dysarthria_female: 500 samples of dysarthric female audio recorded on different sessions. | |
| dysarthria_male: 500 samples of dysarthric male audio recorded on different sessions. | |
| non _dysarthria _female: 500 samples of non-dysarthric female audio recorded on different sessions. | |
| non _dysarthria _male: 500 samples of non-dysarthric male audio recorded on different sessions. | |
| data.csv | |
| filename: audio file path | |
| is_dysarthria: non-dysarthria or dysarthria | |
| gender: male or female | |
| Application of the data, | |
| Applying deep learning technology to classify dysarthria and non-dysarthria patients | |
| References: | |
| Dumane, P., Hungund, B., Chavan, S. (2021). Dysarthria Detection Using Convolutional Neural Network. In: Pawar, P.M., Balasubramaniam, R., Ronge, B.P., Salunkhe, S.B., Vibhute, A.S., Melinamath, B. (eds) Techno-Societal 2020. Springer, Cham. https://doi.org/10.1007/978-3-030-69921-5_45 |