HCMAC Amplitude Spectral Subtraction for Noise Cancellation
The primary advantages of the cerebellar model arithmetic computer (CMAC) are its ability to learn very fast and it can approximate a wide variety of non-linear functions. A comprehensive and efficient technique for speech enhancement based on an extension of the spectral subtraction method and integrating it with the higher order CMAC is developed. In addition, the paper also presents an unsupervised learning of the higher order CMAC as applied to speech enhancement. Simulation results using speech corrupted with very low signal to noise ratio (from -5dB to -20dB) in a vehicular environment using microphone placed on a dashboard in front of the speaker, shows great potential on the application of the HCMAC-ASS for practical application in signal enhancement.
Abdul Wahab Eng Chong Tan H(u)seyin Abut
School of Computer Engineering, Nanyang Technological University,Nanyang Avenue, Singapore 639798, S ECE Department, San Diego State University, San Diego, CA 92182, USA
国际会议
8th International Conference on Neural Information Processing(ICONIP 2001)(第八届国际神经信息处理大会)
上海
英文
115-118
2001-11-14（万方平台首次上网日期，不代表论文的发表时间）