A software system for content-based identification of audio recordings is presented. The system transforms its input using a perceptual model of the human auditory system, making its output robust to lossy compression and to other distortions. In order to make use of both the instantaneous pattern of a recording's perceptual features and the information contained in the evolution of these features over time, the system first matches fragments of the input against a database of fragments of known recordings. In a subsequent step, these matches at the fragment level are assembled in order to identify a single recording that matches consistently over time. In a small-scale test the system has matched all queries successfully against a database of 100 000 commercially released recordings.

Authors: Schmidt, Geoff R.; Belmonte, Matthew K.
Affiliations: Intellivid Corporation, Cambridge, MA, USA; University of Cambridge, Cambridge, UK(See document for exact affiliation information.)
JAES Volume 52 Issue 4 pp. 366-377; April 2004
Publication Date: April 15, 2004

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