Comparative performance evaluation of MMSE-based speech enhancement techniques through simulation and real-time implementation

In this article, a generic model of minimum mean square error (MMSE) based speech enhancement technique has been presented and implemented on the hardware. Models for different MMSE-based methods were obtained by changing the gain function in the generic model. In all the methods, modified cascaded median-based noise estimation method has been used for noise estimation. Performances of all these MMSE-based methods were compared, among themselves and also with the spectral subtraction method for speech enhancement. The results have been evaluated using objective measures, subjective measure and composite objective measures for different noisy speech files. Results, in terms of objective evaluation parameters, indicated that the adaptive β-order MMSE method yielded better performance than the other methods. In subjective quality test (according to MOS listening test), β-order MMSE and adaptive β-order MMSE method yielded high scores. Real-time implementation has been carried out using TMS320C6416T DSP starter kit and code composer studio software. Estimation of memory consumption and execution time has been done for all the methods. © 2018, Springer Science+Business Media, LLC, part of Springer Nature.