A Video Indexing Approach Based on Audio Classification

This paper presents a video indexing approach based only on audio classification. Indeed, we apply to an audio-visual document a set of methods for partitioning the associated audio data into homogeneous segments. The aim is to highlight semantically relevant items of a multimedia document by relying only on simple audio processing techniques. A simple algorithm to identify audio segments belonging to silence, music, speech and noise classes has been proposed.