BUSCADOR RECOLECTA

The repository includes the test datasets used in various audio-score alignment experiments on Ottoman-Turkish makam music. This particular release contains the audio-score alignment test dataset used in the paper: Şentürk, S., Gulati, S., and Serra, X. (2014). Towards alignment of score and audio recordings of Ottoman-Turkish makam music. In Proceedings of 4th International Workshop on Folk Music Analysis, pages 57–60, Istanbul, Turkey.

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. The dataset can be used for training models for each Mridangam stroke.

Audio music content----- They feature 7 varnams in 7 raagas sung by 5 young professional singers who received training for more than 15 years. They are all set to Adi taala. Measuring the intonation variations require absolutely clean pitch contours. For this, all the varṇaṁs are recorded without accompanying instruments, except the drone. Taala annotations----- The recordings are annotated with taala cycles, each annotation marking the starting of a cycle. We have later automatically divided each cycle into 8 equal parts. The annotations are made available as sonic visualizer annotation layers. Each annotation is of the format m.n where m is the cycle number and n is the division within the cycle. All m.1 annotations are manually done, whereas m.[2-8] are automatically labelled. Notations----- The notations for 7 varnams are procured from an archive curated by Shivkumar, in word document format. They are manually converted to a machine readable format (yaml). Each file is essentially a dictionary with section names of the composition as keys. Each section is represented as a list of cycles. Each cycle in turn has a list of divisions. Possible uses of the dataset----- The distinct advantage of this dataset is the free availability of the audio content. Along with the annotations, it can be used for melodic analyses: characterizing intonation, motif discovery and tonic identification. The availability of a machine readable notation files allows the dataset to be used for audio-score alignment.

These datasets comprise audio excerpts and manually done annotations of the tonic pitch of the lead artist for each audio excerpt. Each excerpt is accompanied by its associated editorial metadata. These datasets can be used to develop and evaluate computational approaches for automatic tonic identification in Indian art music. These datasets have been used in several articles mentioned below. A majority of these datasets come from the CompMusic corpora of Indian art music, for which each recording is associated with a MBID. With the MBID other information can be obtained using the Dunya API. We here provide an overview of the tonic identification datasets. Datasets ------- The statistics about the datasets for tonic identification is listed in the table below. These six datasets are used in Gulati, S., Bellur, A., Salamon, J., Ranjani, H. G., Ishwar, V., Murthy, H. A., & Serra, X. (2014). Automatic Tonic Identification in Indian Art Music: Approaches and Evaluation. Journal of New Music Research, 43(01), 55–73 for a comparative evaluation. To the best of our knowledge these are the largest datasets available for tonic identification for Indian art music. These datases vary in terms of the audio quality, recording period (decade), the number of recordings for Carnatic, Hindustani, male and female singers and instrumental and vocal excerpts. For a detailed information about these datasets we refer to Chapter 3 of this thesis (http://hdl.handle.net/10803/398984). The audio files corresponding to these datsets are made available on request for only research purposes. To obtain the files fill the FORM (https://goo.gl/forms/kWzpCsZW8DM7noW63). CompMusic Tonic Identification Datasets --- Datasets: CM1, CM2, CM3 Features: pitch + multipitch histogram + pitch histograms IITM Tonic Identification Datasets Datasets: IITM1, IITM2 Features: pitch + multipitch histogram + pitch histograms IISc Tonic identification Dataset Dataset: IISc Features: pitch + multipitch histogram + pitch histograms Annotation Format ---The tonic annotations are availabe both in tsv and json format. TSV: relative path to audio, tonic (Hz), Carnatic or Hindustani, artist_name, gender of the singer, vocal or instrumental JSON: name of the lead artist if available, 'filepath': relative path to the audio file, gender of the lead singer if available, 'mbid': musicbrainz id when available, 'tonic': tonic in Hz, 'tradition': Hindustani or Carnatic, 'type': vocal or instrumental where keys of the main dictionary are the filepaths to the audio files (feature path is exactly the same with a different extension of the file name).

There are 899 SymbTr-scores. The scores were manually annotated into melodic segments by 3 experts. In total, there are 31362 phrase annotations in this dataset.