The Mridangam Stroke dataset is a collection of 7162 audio examples of individual strokes of the Mridangam in various tonics. The dataset comprises of 10 different strokes played on Mridangams with 6 different tonic values. Audio content The dataset provides audio examples for each of the strokes. There are six different tonics and ten different stroke labels. The audio examples were recorded from a professional Carnatic percussionist in a semi-anechoic studio conditions by Akshay Anantapadmanabhan using SM-58 microphones and an H4n ZOOM recorder. The audio was sampled at 44.1 kHz and stored as 16 bit wav files. The dataset can be used for training models for each Mridangam stroke. Metadata The whole dataset is organized by the tonic, into 6 packs. Each audio file is named as, <StrokeName>_<Tonic>_<InstanceNumber>.wav <Tonic> = {B, C, Csh, D, Dsh, E} <StrokeName> = {Bheem, Cha, Dheem, Dhin, Num, Ta, Tha, Tham, Thi, Thom} Using this dataset A detailed description of the Mridangam and its strokes can be found in the following paper. A part of the dataset was used in the paper. Please cite it if you use the dataset in your work. Akshay Anantapadmanabhan, Ashwin Bellur, Hema A. Murthy, "Modal analysis and transcription of strokes of the mridangam using non-negative matrix factorization," in Proc. of the IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2013), pp.181-185, May 2013 http://hdl.handle.net/10230/25756 We are interested in knowing if you find our datasets useful! If you use our dataset please email us at mtg-info@upf.edu and tell us about your research. Contact If you have any questions or comments about the dataset, please feel free to write to us: Akshay Anantapadmanabhan (akshay.anantapadmanabhan@gmail.com) http://compmusic.upf.edu/mridangam-stroke-dataset

{"references": ["Akshay Anantapadmanabhan, Ashwin Bellur, Hema A. Murthy, \"Modal analysis and transcription of strokes of the mridangam using non-negative matrix factorization,\" in Proc. of the IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2013), pp.181-185, May 2013"]}