Guangyu Xia

Active scores: Representation and synchronization in human-computer performance of popular music

Computers have the potential to significantly extend the practice of popular music based on steady tempo and mostly determined form. There are significant challenges to overcome, however, due to constraints including accurate timing based on beats and adherence to a form or structure despite possible changes that may occur, possibly even during performance. We describe an approach to synchronization across media that takes into account latency due to communication delays and audio buffering. We also address the problem of mapping from a conventional score with repeats and other structures to an actual performance, which can involve both “flattening” the score and rearranging it, as is common in popular music. Finally, we illustrate the possibilities of the score as a bidirectional user interface in a real-time system for music performance, allowing the user to direct the computer through a digitally displayed score, and allowing the computer to indicate score position back to human performers.

Methods and prospects for human-computer performance of popular music

Computers are often used in performance of popular music, but most often in very restricted ways, such as keyboard synthesizers where musicians are in complete control, or pre-recorded or sequenced music where musicians follow the computers drums or click track. An interesting and yet little-explored possibility is the computer as highly autonomous performer of popular music, capable of joining a mixed ensemble of computers and humans. Considering the skills and functional requirements of musicians leads to a number of predictions about future human–computer music performance (HCMP) systems for popular music. We describe a general architecture for such systems and describe some early implementations and our experience with them.

MidiFind: Similarity Search and Popularity Mining in Large MIDI Databases

While there are perhaps millions of MIDI files available over the Internet, it is difficult to find performances of a particular piece because well labeled metadata and indexes are unavailable. We address the particular problem of finding performances of compositions for piano, which is different from often-studied problems of Query-by-Humming and Music Fingerprinting. Our MidiFind system is designed to search a million MIDI files with high precision and recall. By using a hybrid search strategy, it runs more than 1000 times faster than naive competitors, and by using a combination of bag-of-words and enhanced Levenshtein distance methods for similarity, our system achieves a precision of 99.5 % and recall of 89.8 %.