Culturally sensitive strategies for automatic music prediction

Thesis (Ph. D.)--Massachusetts Institute of Technology, School of Architecture and Planning, Program in Media Arts and Sciences, 2012.Cataloged from PDF version of thesis.Includes bibliographical references (p. 103-112).Music has been shown to form an essential part of the human experience-every known society engages in music. However, as universal as it may be, music has evolved into a variety of genres, peculiar to particular cultures. In fact people acquire musical skill, understanding, and appreciation specific to the music they have been exposed to. This process of enculturation builds mental structures that form the cognitive basis for musical expectation. In this thesis I argue that in order for machines to perform musical tasks like humans do, in particular to predict music, they need to be subjected to a similar enculturation process by design. This work is grounded in an information theoretic framework that takes cultural context into account. I introduce a measure of musical entropy to analyze the predictability of musical events as a function of prior musical exposure. Then I discuss computational models for music representation that are informed by genre-specific containers for musical elements like notes. Finally I propose a software framework for automatic music prediction. The system extracts a lexicon of melodic, or timbral, and rhythmic primitives from audio, and generates a hierarchical grammar to represent the structure of a particular musical form. To improve prediction accuracy, context can be switched with cultural plug-ins that are designed for specific musical instruments and genres. In listening experiments involving music synthesis a culture-specific design fares significantly better than a culture-agnostic one. Hence my findings support the importance of computational enculturation for automatic music prediction. Furthermore I suggest that in order to sustain and cultivate the diversity of musical traditions around the world it is indispensable that we design culturally sensitive music technology.by Mihir Sarkar.Ph.D

Real-time online musical collaboration system for Indian percussion

Thesis (S.M.)--Massachusetts Institute of Technology, School of Architecture and Planning, Program in Media Arts and Sciences, 2007.Includes bibliographical references (p. 111-119).Thanks to the Internet, musicians located in different countries can now aspire to play with each other almost as if they were in the same room. However, the time delays due to the inherent latency in computer networks (up to several hundreds of milliseconds over long distances) are unsuitable for musical applications. Some musical collaboration systems address this issue by transmitting compressed audio streams (such as MP3) over low-latency and high-bandwidth networks (e.g. LANs or Internet2) to constrain time delays and optimize musician synchronization. Other systems, on the contrary, increase time delays to a musically-relevant value like one phrase, or one chord progression cycle, and then play it in a loop, thereby constraining the music being performed. In this thesis I propose TablaNet, a real-time online musical collaboration system for the tabla, a pair of North Indian hand drums. This system is based on a novel approach that combines machine listening and machine learning. Trained for a particular instrument, here the tabla, the system recognizes individual drum strokes played by the musician and sends them as symbols over the network. A computer at the receiving end identifies the musical structure from the incoming sequence of symbols by mapping them dynamically to known musical constructs. To deal with transmission delays, the receiver predicts the next events by analyzing previous patterns before receiving the original events, and synthesizes an audio output estimate with the appropriate timing. Although prediction approximations may result in a slightly different musical experience at both ends, we find that this system demonstrates a fair level of playability by tabla players of various levels, and functions well as an educational tool.by Mihir Sarkar.S.M