Ανάλυση περιεχομένων ροών ήχου με στόχο την κατάτμηση και ταξινόμηση οπτικοακουστικών δεδομένων

Μπενέτος, Ιωάννης Δ.

Master Thesis

Author

Μπενέτος, Ιωάννης Δ.

Date

2013-02-11

Abstract

The purpose of this work is to implement and investigate the reliability and performance of a method for automatic segmentation and classification of the contents of an audio stream based on audio content analysis. While current approaches for audiovisual data segmentation and classification are mostly focused on visual cues, audio signals may actually play a more important role in content parsing for many applications. An approach to automatic segmentation and classification of audiovisual data based on audio content analysis is proposed. The audio signal from movies or TV programs is segmented and classified into basic types such as speech, music, song, environmental sound, speech with music background, environmental sound with music background, silence, etc. Simple audio features including the energy function, the average zero-crossing rate, the fundamental frequency, and the spectral peak tracks are extracted to ensure the feasibility of real-time processing. A heuristic rule-based procedure is proposed to segment and classify audio signals and built upon morphological and statistical analysis of the time-varying functions of these audio features. Experimental results show that the proposed scheme achieves an accuracy rate of 72% in audio classification.