Playing with Cases: Rendering Expressive Music with Case-Based Reasoning

• Published in: The AI magazine Vol. 33; no. 4; pp. 22 - 32
• Main Authors: DE MANTARAS, Ramon Lopez, LLUIS ARCOS, Josep
• Format: Journal Article
• Language: English
• Published: Menlo Park, CA American Association for Artificial Intelligence 22.12.2012; John Wiley & Sons, Inc
• Subjects: Acoustics; Applied sciences; Artificial intelligence; Audition; Biological and medical sciences; Computer music; Computer science; control theory; systems; Creativity; Emotions; Exact sciences and technology; Fundamental and applied biological sciences. Psychology; Fundamental areas of phenomenology (including applications); Human performance; Knowledge-based system; Knowledge-based systems; Methods; Music; Music and musical intruments; Musical performances; Musicians & conductors; Neural networks; Perception; Physics; Psychology. Psychoanalysis. Psychiatry; Psychology. Psychophysiology; Reasoning; Sound; Studies; Transduction; acoustical devices for the generation and reproduction of sound; Spain; Sound recording; Rhythm; Case based reasoning; Long term; Music synthesis; Hearing; Musician; Music; Musical acoustics; Gesture; Audio acoustics; Artificial intelligence; Sound record
• ISSN: 0738-4602; 2371-9621
• DOI: 10.1609/aimag.v33i4.2405

This article surveys long-term research on the problem of rendering expressive music by means of AI techniques with an emphasis on case-based reasoning (CBR). Following a brief overview discussing why people prefer listening to expressive music instead of nonexpressive synthesized music, we examine a representative selection of well-known approaches to expressive computer music performance with an emphasis on AI-related approaches. In the main part of the article we focus on the existing CBR approaches to the problem of synthesizing expressive music, and particularly on TempoExpress, a case-based reasoning system developed at our Institute, for applying musically acceptable tempo transformations to monophonic audio recordings of musical performances. Finally we briefly describe an ongoing extension of our previous work consisting of complementing audio information with information about the gestures of the musician. Music is played through our bodies, therefore capturing the gesture of the performer is a fundamental aspect that has to be taken into account in future expressive music renderings. This article is based on the "2011 Robert S. Engelmore Memorial Lecture" given by the first author at AAAI/IAAI 2011.