Abstract
This chapter presents the application of compressive sensing (CS) theory for compression of a speech signal. The speech signal is first converted into its sparse coefficients using a signal transform. Then compressed sparse measurements of the speech signal are generated using its sparse coefficients and a measurement matrix, generated using normal Gaussian distribution. The compressed speech signal is reconstructed from its compressed sparse measurements using various CS reconstruction algorithms. In this chapter, two greedy CS reconstruction algorithms – orthogonal matching pursuit (OMP) and compressive sensing matching pursuit (COSAMP) – are used for generation of a compressed speech signal.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Bibliography
Abo-Zahhad M, Hussein A, Mohamed M (2015) Compression of ECG signal based on compressive sensing and the extraction of significant features. Int J Commun Netw Syst Sci 8:97–117
Desai N, Naitik N (2014) Evaluating performance of compressive sensing for speech signal with various basis. Int J Comput Appl 94(11):23–26
Mishra A, Thakkar F, Modi C, Kher R (2012) ECG signal compression using compressive sensing and wavelet transform. In: Proceedings of 2012 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, IEEE, San Diego, pp 3404 – 3407
Moreno-Alvarado R, Martinez-Garcia M (2011) DCT-compressive sampling of frequency sparse audio signals. In: Proceedings of the world congress on engineering, vol 2, pp 6–8
Sun L, Mkwawa I, Jammeh E, Ifeachor E (2013) Speech compression. In: Guide to voice and video over IP computer communications and networks. Springer, London, pp 23–51
Zhou Y, Zhao H (2013) Speech signal compressed sensing based on KSVD adaptive dictionary. J Theor Appl Inf Technol 48(2):1237–1243
Author information
Authors and Affiliations
Rights and permissions
Copyright information
© 2018 The Author(s)
About this chapter
Cite this chapter
Thanki, R., Borisagar, K., Borra, S. (2018). Speech Compression Technique Using Compressive Sensing Theory. In: Advance Compression and Watermarking Technique for Speech Signals. SpringerBriefs in Electrical and Computer Engineering(). Springer, Cham. https://doi.org/10.1007/978-3-319-69069-8_4
Download citation
DOI: https://doi.org/10.1007/978-3-319-69069-8_4
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-69068-1
Online ISBN: 978-3-319-69069-8
eBook Packages: EngineeringEngineering (R0)