Abstract
Due to fewer researches and applications of speech compressed sensing, the sparsity of speech signals was studied first. Then the Fourier orthogonal transform method and the Orthogonal Matching Pursuit (OMP) algorithm were used to compress and reconstruct speech signals. The relationship between the signal reconstruction and its performance, such as the speech signal compression ratio, the periodicity of reconstructed signals, and the frame size etc. is also discussed here. Experiments have shown that: (1) voice signal is sparse and compressible; (2) the speech reconstruction of integral period and regular periodicity signals performs better than that of non integral period and irregular periodicity signals; (3) the best frame size of reconstructed speech is about 10ms.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
