Computer audition

Computer audition (CA) or machine listening is the general field of study of algorithms and systems for audio interpretation by machines.[1][2] Since the notion of what it means for a machine to "hear" is very broad and somewhat vague, computer audition attempts to bring together several disciplines that originally dealt with specific problems or had a concrete application in mind. The engineer Paris Smaragdis, interviewed in Technology Review, talks about these systems — "software that uses sound to locate people moving through rooms, monitor machinery for impending breakdowns, or activate traffic cameras to record accidents."[3]

Inspired by models of human audition, CA deals with questions of representation, transduction, grouping, use of musical knowledge and general sound semantics for the purpose of performing intelligent operations on audio and music signals by the computer. Technically this requires a combination of methods from the fields of signal processing, auditory modelling, music perception and cognition, pattern recognition, and machine learning, as well as more traditional methods of artificial intelligence for musical knowledge representation.[4][5]

  1. ^ Machine Audition: Principles, Algorithms and Systems. IGI Global. 2011. ISBN 9781615209194.
  2. ^ "Machine Audition: Principles, Algorithms and Systems" (PDF).
  3. ^ Paris Smaragdis taught computers how to play more life-like music
  4. ^ Tanguiane (Tangian), Andranick (1993). Artificial Perception and Music Recognition. Lecture Notes in Artificial Intelligence. Vol. 746. Berlin-Heidelberg: Springer. ISBN 978-3-540-57394-4.
  5. ^ Tanguiane (Tanguiane), Andranick (1994). "A principle of correlativity of perception and its application to music recognition". Music Perception. 11 (4): 465–502. doi:10.2307/40285634. JSTOR 40285634.