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Convention Paper

Investigation of Salient Audio-Features for Pattern-Based Semantic Content Analysis of Radio Productions

Authors: Kotsakis, Rigas; Kalliris, George; Dimoulas, Charalampos

AES Convention 132 · Paper 8663 · April 2012

Abstract

The paper focuses on the investigation of salient audio features for pattern-based semantic analysis of radio programmes. Most news and music radio programmes have many structure similarities with respect to the appearance of different content types. Speech and music are continuously interchanged and overlapped, whereas specific speakers and voice patterns are more important to recognize. Recent research showed that various taxonomies and hierarchical classification schemes can be effectively deployed in combination with supervised and unsupervised training for semantic audio content analysis. Undoubtedly, audio feature extraction and selection is very important for the success of the finally trained expert system. The current paper employs feature ranking algorithms, investigating audio features saliency in various classification taxonomies of radio production content.

Details

Published in
AES Convention 132
AES Convention
132
Paper number
8663
Publication date
April 6, 2012
Session subject
Education, Human Factors, and Applications
Affiliation
Aristotle University of Thessaloniki, Thessaloniki, Greece (See document for exact affiliation information.)
Type
Convention Paper