@inproceedings{
 title = {A survey on recent advances in speech compressive sensing},
 type = {inproceedings},
 year = {2013},
 keywords = {Compressive sensing,data acquisition,recovery algorithm,sparsity,speech synthesis},
 id = {c7bddaef-189b-321b-a351-c21d743e1d01},
 created = {2018-09-06T11:22:40.476Z},
 file_attached = {false},
 profile_id = {11ae403c-c558-3358-87f9-dadc957bb57d},
 last_modified = {2018-09-06T11:22:40.476Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {false},
 hidden = {false},
 private_publication = {false},
 abstract = {Compressive sensing (CS) is one of the upcoming fields which have paved its way for different approaches towards the signal acquisition and processing systems. In past years, many fields of application have emerged, where speech is one of the most popular one. Due to stochastic nature of speech signal, we are still in search for a proper sparse representation of the signal, so that we could easily incorporate CS and thereby reduce the increasing burden on the ADC. In this paper, we discuss some of the works which have been carried out towards the sparse representation of the speech signals. The idea is to concatenate them on a common platform by exploiting the signal and its basis matrices. Each of the approaches has its own pros and corns for the sparse representation. © 2013 IEEE.},
 bibtype = {inproceedings},
 author = {Shukla, U.P. and Patel, N.B. and Joshi, A.M.},
 doi = {10.1109/iMac4s.2013.6526422},
 booktitle = {Proceedings - 2013 IEEE International Multi Conference on Automation, Computing, Control, Communication and Compressed Sensing, iMac4s 2013}
}

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