Speech compression using compressive sensing on a multicore system by Gunawan, Teddy Surya, Khalifa, Othman Omran, Shafie, Amir Akramin, Ambikairajah, Eliathamby

“…In this paper, a novel algorithm for speech coding utilizing CS principle is developed. The sparsity of speech signals is exploited using gammatone filterbank and Discrete Cosine Transform (DCT) in which the compressive sensing principle is then applied to the sparse subband signals. …”
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Objective evaluation of speech enhancement using compressive sensing algorithm by Sulong, Amart, Gunawan, Teddy Surya, Khalifa, Othman Omran, Chebil, Jalel

“…The CS algorithm, can directly acquire compressed data signals and replace samples by more general measurements of the uniform rate digitization with signal sparsity model. Perceptual evaluation of speech quality (PESQ) is an objective evaluation of speech enhancement algorithm used to measure the enhanced speech quality. …”
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Study on sparseness effects over NMF applied for automatic text summarization by Batcha, Nowshath Kadhar, Murugesan, Raja Kumar, A. Aziz, Normaziah

“…In this study on NMF algorithm that supports sparseness is treated with various degree of sparsity and its performance impact on text summary generated is compared with other NMF algorithms without sparseness constraints.…”
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Speech enhancement based on compressive sensing algorithm by Sulong, Amart, Gunawan, Teddy Surya, Khalifa, Othman Omran, Chebil , Jalel

“…Using CS can reduce the number of degrees of freedom of a sparse/compressible signal by permitting only certain configurations of the large and zero/small coefficients, and structured sparsity models. Therefore, CS is significantly provides a way of reconstructing a compressed version of the speech in the original signal by taking only a small amount of linear and non-adaptive measurement. …”
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