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Voice Command II: A DSP Implementation of Robust Speeth Recognition in Real-World Noisy Environments

机译:语音命令II:DSP在实际嘈杂环境中实现强大的Speeth认可

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摘要

The "Voice Command" system. designed for isolated word recognition tasks in real-world noisy environments. was implemented on a fixed-point DSP board to operate in real-time. Simple auditory model, ie., zero-crossings with peak amplitudes (ZCPA) model, is used for noise-robust feature extraction, and neural network classifier recognizes input patterns.The system performance is further improved by incorporating speaker adaptation and out-of-vocabulary word rejection capabilities. The radial basis function (RBF) classifier provides better sefjection performance than multi-layer perceptron (MLP) classifiers.
机译:“语音命令”系统。 专为真实世界嘈杂环境中的孤立字识别任务而设计。 在固定点DSP板上实施以实时运行。 简单的听觉模型,即,具有峰值幅度(ZCPA)模型的零点,用于噪声鲁棒特征提取,并且神经网络分类器识别输入模式。通过结合扬声器适应和OUT - OUT-进一步提高了系统性能。 词汇拒绝能力。 径向基函数(RBF)分类器提供比多层Perceptron(MLP)分类器更好的SEF注意性性能。

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