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A Hybrid Genetic-Neural Front-End Extension for Robust Speech Recognition over TelephoneLines

机译:关于尺寸强大的语音识别的混合遗传 - 神经前端延伸

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This paper presents a hybrid technique combining the Karhonen-Loeve Transform (KLT), the Multilayer Perceptron (MLP) and Genetic Algorithms (GAs) to obtain less-variant Mel-frequency parameters. The advantages of such an approach are that the robustness can be reached without modifying the recognition system, and that neither assumption nor estimation of the noise are required. To evaluate the effectiveness of the proposed approach, an extensive set of continuous speech recognition experiments are carried out by using the NTIMIT telephone speech database. The results show that the proposed approach outperforms the baseline and conventional systems.
机译:本文提出了一种混合技术,将Karhonen-Loeve变换(KLT),多层感知(MLP)和遗传算法(气体)组合以获得较少变体的熔融频率参数。这种方法的优点是可以在不修改识别系统的情况下达到鲁棒性,并且既不需要假设也不需要估计噪声。为了评估所提出的方法的有效性,通过使用NTIMIT电话语音数据库进行广泛的连续语音识别实验。结果表明,该方法优于基线和常规系统。

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