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This dataset is a collection of mel-spectrogram features extracted from Indian regional music containing the following languages: Hindi, Gujarati, Marathi, Konkani, Bengali, Oriya, Kashmiri, Assamese, Nepali, Konyak, Manipuri, Khasi & Jaintia, Tamil, Malayalam, Punjabi, Telugu, Kannada. Five recordings are collected for each language for four artists (2Male + 2Female) each. 2 artists out of 4 for each language are old veteran performers, and the remaining 2 are contemporary performers. Overall, the dataset includes 17 languages and 68 artists (34 Males and 34 Females). There are 340 recordings in the dataset, with a total duration of 29.3 hrs. Mel-spectrogram is extracted from a 1-second segment with a 1/2 second sliding window for each song. Extracted mel-spectrogram for each segment is annotated with language, location, local_song_index, global_song_index, language_id, location_id, artist_id, gender_id and no_of_artists. _________________________________________________________________________________________________________ This project was funded under the grant number: ECR/2018/000204 by the Science & Engineering Research Board (SERB).
Data-driven approach for music, Deep Learning, Indian Music, Regional Music, Music, Dataset
Data-driven approach for music, Deep Learning, Indian Music, Regional Music, Music, Dataset
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