Ajay Srinivasamurthy

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We present an audio chord recognition system based on a generalization of the Hidden Markov Model (HMM) in which the duration of chords is explicitly considered-a type of HMM referred to as a hidden semi-Markov model, or duration-explicit HMM (DHMM). We find that such a system recognizes chords at a level consistent with the state-of-the-art systems –(More)
In this paper, we approach the tasks of beat tracking, down-beat recognition and rhythmic style classification in non-Western music. Our approach is based on a Bayesian model, which infers tempo, downbeats and rhythmic style, from an audio signal. The model can be automatically adapted to rhythmic styles and time signatures. For evaluation , we compiled and(More)
In many cultures of the world, traditional percussion music uses mnemonic syllables that are representative of the tim-bres of instruments. These syllables are orally transmitted and often provide a language for percussion in those music cultures. Percussion patterns in these cultures thus have a well defined representation in the form of these syllables ,(More)
A supervised approach to metrical cycle tracking from audio is presented , with a main focus on tracking the tāḷa, the hierarchical cyclic metrical structure in Carnatic music. Given the tāḷa of a piece, we aim to estimate the akṣara (lowest metrical pulse), the akṣara period, and the sama (first pulse of the tāḷa cycle). Starting with percussion enhanced(More)
Tok! is a collaborative acoustic instrument application for iOS devices aimed at real time percussive music making in a co-located setup. It utilizes the mobility of hand-held devices and transforms them into drumsticks to tap on flat surfaces and produce acoustic music. Tok! is also networked and consists of a shared interactive music score to which the(More)