Speech coding is a representation of a digitized speech signal using as few bits as possible while maintaining reasonable level of speech quality. Due to an increasing need for bandwidth conservation in wireless communication, research in speech coding has intensified. Compressive sensing (CS) is a technique that has recently gained much attention in many different areas and applications, such as Signal processing, imaging, speech recognition, data acquisition, and is being recently used in speech compression for sparse channel. In this paper, a design and implementation of speech codec based on the CS technique is introduced. Since CS performs well in sparse signals, different sparsifying transforms are analysed and compared using Gini coefficient. The quality of the speech coder is evaluated using Perceptual Evaluation of Speech Quality (PESQ) and subjective listening tests. Results show that the speech coders have achieved a PESQ score of 3.16 at 4 kbps which is a good quality as listening tests confirms. The coder is also compared with Code Excited Linear Prediction (CELP) coder.

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