Soundspotter - A Prototype System for Content-based Audio Retrieval

Christian Spevak; Emmanuel Favreau
DAFx-2002 - Hamburg
We present the audio retrieval system “Soundspotter,” which allows the user to select a specific passage within an audio file and retrieve perceptually similar passages. The system extracts framebased features from the sound signal and performs pattern matching on the resulting sequences of feature vectors. Finally, an adjustable number of best matches is returned, ranked by their similarity to the reference passage. Soundspotter comprises several alternative retrieval algorithms, including dynamic time warping and trajectory matching based on a self-organizing map. We explain the algorithms and report initial results of a comparative evaluation.