TY - JFULL AU - Harish Chander and Balwinder Singh and Ravinder Khanna PY - 2017/8/ TI - Subjective Evaluation of Spectral and Time Domain Cascading Algorithm for Speech Enhancement for Mobile Communication T2 - International Journal of Electronics and Communication Engineering SP - 936 EP - 941 VL - 11 SN - 1307-6892 UR - https://publications.waset.org/pdf/10008232 PU - World Academy of Science, Engineering and Technology NX - Open Science Index 127, 2017 N2 - In this paper, we present the comparative subjective analysis of Improved Minima Controlled Recursive Averaging (IMCRA) Algorithm, the Kalman filter and the cascading of IMCRA and Kalman filter algorithms. Performance of speech enhancement algorithms can be predicted in two different ways. One is the objective method of evaluation in which the speech quality parameters are predicted computationally. The second is a subjective listening test in which the processed speech signal is subjected to the listeners who judge the quality of speech on certain parameters. The comparative objective evaluation of these algorithms was analyzed in terms of Global SNR, Segmental SNR and Perceptual Evaluation of Speech Quality (PESQ) by the authors and it was reported that with cascaded algorithms there is a substantial increase in objective parameters. Since subjective evaluation is the real test to judge the quality of speech enhancement algorithms, the authenticity of superiority of cascaded algorithms over individual IMCRA and Kalman algorithms is tested through subjective analysis in this paper. The results of subjective listening tests have confirmed that the cascaded algorithms perform better under all types of noise conditions. ER -