ASE-CMAC for speech enhancement in a vehicular environment
Abdul Wahab, Chai Hiok Quek, Eng-Chong Tan · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2000
CMAC (Cerebellar Model Arithmetic Computer) have attractive properties of learning convergence and speed and can be ideal in the use of speech processing and enhancement. Many studies have used this special type of neural networks that imitate the human cerebellum in learning control and demonstrated successful results. In this paper CMAC is used to model the speech and noise pick up from a microphone in a vehicular environment. For storage and retrieval of learned data, the input speech and noise signals are quantized using the traditional equal-size quantization region. Results of the modeling were compared to that using the variable size amplitude spectral estimator (ASE). In addition speech enhancement simulations were also presented using the adaptive LMS-CMAC and the ASE-CMAC algorithm and have shown potential for real-time application. The ASE-CMAC produce a far better result especially in areas where the signal to noise ration is very low.