Paul Lamere writes about the field of Music Information Retrieval (MIR)- a fairly new field, rivalling and perhaps even exceeding the field of speech recognition in terms of the technical challenges. Excerpts with edits:
Successful MIR researchers typically need to master signal processing, machine learning, symbolic representation, search techniques, pattern classification as well as music theory. Advances in speech recognition over the years have been aided by the availability of a number of freely available toolkits such as HTK, ISIP and the Sphinx family of recognition engines. Just as with speech recognition, the availability of good tools will help advance the state of art of music information retrieval. M2K is an open-sourced Java-based framework designed to allow Music Information Retrieval researchers to rapidly prototype, share and scientifically evaluate and has been just released.
M2K comes with a large set of MIR specific modules, (currently oriented toward audio-content-based analysis), as well as a number of sample itineraries (an itinerary a task-oriented configuration of modules). M2K builds upon the D2K data mining framework developed by the Automated Learning Group at the NCSA. M2K is open source, the code is well written by folks who understand MIR. M2K provides bridges to other toolkits such as Marsyas, and Matlab. Perhaps most important, M2K has a tie-in to the IMRISEL which will soon be hosting a large collection of music (in audio as well as symbolic form) that will serve as a resource for MIR researchers. This is key to MIR researchers since getting access to large bodies of music can be very difficult and expensive. The Music and in general entertainment industry is making rapid advances and research and tools like these would help improvements in a significant way.
Category : Entertainment
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