Sankalp Gulati

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We present Essentia 2.0, an open-source C++ library for audio analysis and audio-based music information retrieval released under the Affero GPL license. It contains an extensive collection of reusable algorithms which implement audio input/output functionality, standard digital signal processing blocks, statistical characterization of data, and a large set(More)
The tonic is a fundamental concept in Indian classical music since it constitutes the base pitch from which a lead performer constructs the melodies, and accompanying instruments use it for tuning. This makes tonic identification an essential first step for most automatic analyses of Indian classical music, such as intonation and melodic analysis, and raga(More)
Tonic is a fundamental concept in many music traditions and its automatic identification should be relevant for establishing the reference pitch when we analyse the melodic content of the music. In this paper, we present two methodologies for the identification of the tonic in audio recordings of makam music of Turkey, both taking advantage of some score(More)
The automatic classification of musical genre from audio signals has been a topic of active research in recent years. Although the identification of genre is a subjective task that likely involves high-level musical attributes such as instrumentation, style, rhythm and melody, low-level acoustic features have been widely applied to the automatic task with(More)
We present Essentia 2.0, an open-source C++ library for audio analysis and audio-based music information retrieval released under the Affero GPL license. It contains an extensive collection of reusable algorithms which implement audio input/output functionality, standard digital signal processing blocks, statistical characterization of data, and a large set(More)
Discovery of repeating structures in music is fundamental to its analysis, understanding and interpretation. We present a data-driven approach for the discovery of shorttime melodic patterns in large collections of Indian art music. The approach first discovers melodic patterns within an audio recording and subsequently searches for their repetitions in the(More)
We perform a comparative evaluation of methodologies for computing similarity between short-time melodic fragments of audio recordings of Indian art music. We experiment with 560 different combinations of procedures and parameter values. These include the choices made for the sampling rate of the melody representation, pitch quantization levels,(More)
Raaga is the spine of Indian classical music. It is the single most crucial element of the melodic framework on which the music of the subcontinent thrives. Naturally, automatic raaga recognition is an important step in computational musicology as far as Indian music is considered. It has several applications like indexing Indian music, automatic note(More)
Detecting the occurrences of rāgs’ characteristic melodic phrases from polyphonic audio recordings is a fundamental task for the analysis and retrieval of Indian art music. We propose an abstraction process and a complexity weighting scheme which improve melodic similarity by exploiting specific melodic characteristics in this music. In addition, we propose(More)