Fast Dictionary Learning for Sparse Representations of Speech Signals

Bharathi

Fast Dictionary Learning for Sparse Representations of Speech Signals

Bharathi * §

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§ Kingas College London, London, U.K

Fast Dictionary Learning for Sparse Representations of Speech Signals

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Abstract

For dictionary-based decompositions of certain types, it has been observed that there might be a link between sparsity in the dictionary and sparsity in the decomposition. Sparsity in the dictionary has also been associated with the derivation of fast and efficient dictionary learning algorithms. Therefore, in this paper we present a greedy adaptive dictionary learning algorithm that sets out to find sparse atoms for speech signals. The algorithm learns the dictionary atoms on data frames taken from a speech signal. It iteratively extracts the data frame with minimum sparsity index, and adds this to the dictionary matrix. The contribution of this atom to the data frames is then removed, and the process is repeated. The algorithm is found to yield a sparse signal decomposition, supporting the hypothesis of a link between sparsity in the decomposition and dictionary. The algorithm is applied to the problem of speech representation and speech denoising, and its performance is compared to other existing methods.

References

29 Cites in Article

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Funding

No external funding was declared for this work.

Conflict of Interest

The authors declare no conflict of interest.

Ethical Approval

No ethics committee approval was required for this article type.

Data Availability

Not applicable for this article.

How to Cite This Article

Bharathi. 2014. "Fast Dictionary Learning for Sparse Representations of Speech Signals". Global Journal of Computer Science and Technology - E: Network, Web & Security GJCST-E Volume 14 (GJCST Volume 14 Issue E8).

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GJCST Volume 14 Issue E8

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Journal Specifications

Crossref Journal DOI 10.17406/gjcst

Print ISSN 0975-4350

e-ISSN 0975-4172

Keywords

adaptive dictionary dictionary learning sparse decomposition sparse dictionary speech analysis speech denoising

Classification

GJCST-E Classification I.2.6

Submission ReceivedDecember 6, 2013
Peer Review Double Blind
Handling Editor
Accepted January 3, 2014
Published December 30, 2014

Version of record

v1.2

Issue date

December 30, 2014

Language

English

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Total Score: 132

Country: United Kingdom

Subject: Global Journal of Computer Science and Technology - E: Network, Web & Security

Authors: Maria G. Jafari, Mark D. Plumbley (PhD/Dr. count: 0)

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