论文信息 - Robust speech recognition using fuzzy matrix quantisation and neural networks

Robust speech recognition using fuzzy matrix quantisation and neural networks

The paper considers a new and robust isolated word speech recognition (IWSR) structure that employs FMQ as the spectral labelling process followed by a multilayer perceptron neural network (MLP-NN) classifier. Both elements of the system are designed optimally for operation at a variety of input SNR conditions, when speech is corrupted by car acoustic noise. The proposed scheme and associated system training methodology results in a particularly high recognition performance at input SNR levels as low as 5 and 0 dB. Its 95.13%, speaker dependent (SD) recognition accuracy obtained at 20 dB SNR is only reduced to 88.46% at the rather extreme case of 0 dB SNR.

Lin Cong | C. S. Xydeas

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