Title
Optimal Short-Time Features for Music/Speech Classification of Compressed Audio Data
Abstract
This paper deals with the Music/Speech classification problem, starting from a set of features extracted directly from compressed audio data. The proposed classification system is able to label audio sequences stored as compressed MPEG layer III files. Decoding and analyzing in a unique stage is a fundamental tool for audio streaming applications, such as real time classification. Moreover, the techniques described herein provide useful tools in the management (data tagging, summarization, etc.) of a digital music library. The adopted set of short-time features are computed from the spectral information available in the decoding stage. In this paper, we show that for the classification problem at hand this set of features is redundant and can be dramatically pruned. To this aim we used an optimization strategy based on principal component analysis and genetic algorithms. The results show a very interesting classification accuracy using just one short-time feature.
Year
DOI
Venue
2006
10.1109/CIMCA.2006.160
CIMCA/IAWTIC
Keywords
Field
DocType
audio data,audio sequence,paper deal,interesting classification accuracy,proposed classification system,optimal short-time features,decoding stage,short-time feature,classification problem,compressed audio data,speech classification problem,real time classification,speech classification,feature extraction,data compression,genetic algorithms,principal component analysis,classification system,real time,speech processing,digital music,music,genetic algorithm
Automatic summarization,Speech processing,Pattern recognition,Audio mining,Computer science,Feature extraction,Speech recognition,Digital audio,Artificial intelligence,Decoding methods,Data compression,Genetic algorithm
Conference
ISBN
Citations 
PageRank 
0-7695-2731-0
3
0.38
References 
Authors
4
4
Name
Order
Citations
PageRank
Alfred A. Rizzi11208179.03
Buccino, M.230.38
Panella, M.330.71
Uncini, A.430.38