Create README.md

README.md

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+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