Fuzzy Logic Speech/Non-speech Discrimination for Noise Robust Speech Processing
作者： Rafael Culebras , Javier Ramírez , Juan Manuel Górriz , José C Segura
DOI: 10.1007/11758501_55
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摘要: This paper shows a fuzzy logic speech/non-speech discrimination method for improving the performance of speech processing systems working in noise environments. The system is based on Sugeno inference engine with membership functions defined as combination two Gaussian functions. rule base consists ten if then statements terms denoised subband signal-to-noise ratios (SNRs) and zero crossing rates (ZCRs). Its operation optimized by means hybrid training algorithm combining least-squares backpropagation gradient descent function parameters. experiments conducted Spanish SpeechDat-Car database that proposed yields clear improvements over set standardized VADs discontinuous transmission (DTX) distributed recognition (DSR) also recently published VAD methods.
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