We present a correlation-based algorithm for the agglomerative clus-tering of atoms in sparse atomic decompositions of audio signals. Our goal is to demonstrate useful relationships between elements of the decomposition and the content of the original signal, for such purposes as analysis and modification. We evaluate the performance of the agglomeration algorithm using decompositions of synthetic and real audio signals, and discuss possible extensions of this work. Index Terms — Clustering methods, signal analysis, signal res-olution, time-frequency analysis. 1
Sparse representations are becoming an increasingly useful tool in the analysis of musical audio sig...
Sparse representations are becoming an increasingly useful tool in the analysis of musical audio sig...
In this paper, we have addressed the issue of the sparse compression complexity for the speech signa...
Signal modeling techniques ranging from basis expansions to parametric approaches have been applied ...
In this paper, a new class of audio representations is introduced, together with a corresponding fas...
algorithm for the decomposition of signals. The MMP is a prac-tical solution which introduces the no...
International audienceIn this paper, a new class of audio representations is introduced, together wi...
Sparse and structured signal expansions on dictionaries (i.e. a collection of elementary wave-forms,...
This dissertation makes contributions to the sparse approximation and efficient representation of co...
Abstract—Sparse atomic decomposition algorithms, such as matching pursuit, attempt to find an effici...
Time-frequency representations are commonly used tools for the representation of audio and in partic...
Computational Auditory Scene Analysis (CASA) is challenging problem for which many different approac...
Many natural signals of practical interest are inherently sparse (or at least highly compressible) i...
Abstract—Sparse representations have proved a powerful toolin the analysis and processing of audio s...
This article deals with the generation of auditory-inspired spectro-temporal fea-tures aimed at audi...
Sparse representations are becoming an increasingly useful tool in the analysis of musical audio sig...
Sparse representations are becoming an increasingly useful tool in the analysis of musical audio sig...
In this paper, we have addressed the issue of the sparse compression complexity for the speech signa...
Signal modeling techniques ranging from basis expansions to parametric approaches have been applied ...
In this paper, a new class of audio representations is introduced, together with a corresponding fas...
algorithm for the decomposition of signals. The MMP is a prac-tical solution which introduces the no...
International audienceIn this paper, a new class of audio representations is introduced, together wi...
Sparse and structured signal expansions on dictionaries (i.e. a collection of elementary wave-forms,...
This dissertation makes contributions to the sparse approximation and efficient representation of co...
Abstract—Sparse atomic decomposition algorithms, such as matching pursuit, attempt to find an effici...
Time-frequency representations are commonly used tools for the representation of audio and in partic...
Computational Auditory Scene Analysis (CASA) is challenging problem for which many different approac...
Many natural signals of practical interest are inherently sparse (or at least highly compressible) i...
Abstract—Sparse representations have proved a powerful toolin the analysis and processing of audio s...
This article deals with the generation of auditory-inspired spectro-temporal fea-tures aimed at audi...
Sparse representations are becoming an increasingly useful tool in the analysis of musical audio sig...
Sparse representations are becoming an increasingly useful tool in the analysis of musical audio sig...
In this paper, we have addressed the issue of the sparse compression complexity for the speech signa...