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, downbeat recognition and rhythmic style classification in nonWestern 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 tala, the hierarchical cyclic metrical structure in Carnatic music. Given the tala of a piece, we aim to estimate the aksara (lowest metrical pulse), the aksara period, and the sama (first pulse of the tala cycle). Starting with percussion enhanced(More)
The aim of this paper is to identify and discuss various methods in computational rhythm description of Carnatic and Hindustani music of India, and Makam music of Turkey. We define and describe three relevant rhythm annotation tasks for these cultures beat tracking, meter estimation, and downbeat detection. We then evaluate several methodologies from the(More)
Recent approaches in meter tracking have successfully applied Bayesian models. While the proposed models can be adapted to different musical styles, the applicability of these flexible methods so far is limited because the application of exact inference is computationally demanding. More efficient approximate inference algorithms using particle filters (PF)(More)
Research corpora are representative collections of data and are essential to develop data-driven approaches in Music Information Research (MIR). We address the problem of building research corpora for MIR in Indian art music traditions of Hindustani and Carnatic music, considering several relevant criteria for building such corpora. We also discuss a(More)
Note onset detection and instrument recognition are two of the most investigated tasks in Music Information Retrieval (MIR). Various detection methods have been proposed in previous research for western music, with less focus on other music cultures of the world. In this paper, we focus on onset detection for percussion instruments in Beijing Opera, a major(More)
In many cultures of the world, traditional percussion music uses mnemonic syllables that are representative of the timbres 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)
To my fiancé, Sol Ie iv ACKNOWLEDGEMENTS First, I like to express my sincere gratitude to Dr. Jason Freeman, my advisor, who not only supported me throughout my study at Georgia Tech, but also shared his expertise in music and research unconditionally for this work. I would not have started this research without inspirations he gave me in and out of the(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 periodicity of a musical piece. From this information, we can then obtain(More)