Evaluating performance of Compressed Sensing for speech signals

Author

Abrol, Vinayak ; Sharma, Parmanand ; Budhiraja, S.

Author_Institution

Univ. Inst. of Eng. &Technol., Panjab Univ., Chandigarh, India

fYear

2013

fDate

22-23 Feb. 2013

Firstpage

1159

Lastpage

1164

Abstract

Reconstruction of a signal based on Compressed Sensing (CS) framework relies on the knowledge of the sparse basis & measurement matrix used for sensing. While most of the studies so far focus on the application of CS in fields of images, radar, astronomy etc.; we present our work on application of CS in field of speech/Audio processing. This work shows a comparative analysis of different sparse basis & measurement matrices which can be used in speech/audio processing. Our work gives a detail analysis of the performance bounds, compression ratios, reconstruction errors etc. which should be taken care of while designing CS based speech applications.

Keywords

audio signal processing; compressed sensing; signal reconstruction; speech processing; CS framework; audio processing; compressed sensing; compression ratio; measurement matrix; performance bound; reconstruction error; signal reconstruction; sparse basis matrix; speech processing; speech signal; Compressed sensing; Discrete Fourier transforms; Discrete cosine transforms; Sensors; Sparse matrices; Speech; Speech processing; Compressed sensing; Sensing efficiency; Speech processing; sparse basis;

fLanguage

English

Publisher

ieee

Conference_Titel

Advance Computing Conference (IACC), 2013 IEEE 3rd International

Conference_Location

Ghaziabad

Print_ISBN

978-1-4673-4527-9

Type

conf

DOI

10.1109/IAdCC.2013.6514391

Filename

6514391