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)
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)
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)
In this paper, we propose a beat tracking and beat similarity based approach to rhythm description in Indian Classical Music. We present an algorithm that uses a beat similarity matrix and inter onset interval histogram to automatically extract the sub-beat structure and the long-term periodic-ity of a musical piece. From this information, we can then(More)
Previous research has shown that ensembles of variable length Markov models (VLMMs), known as Multiple Viewpoint Models (MVMs), can be used to predict the continuation of Western tonal melodies, and outperform simpler, fixed-order Markov models. Here we show that this technique can be effectively applied to predicting melodic continuation in North Indian(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)