1、

Research on the HNR Separation of Voice Source with Harmonic Noise

嗓音源谐波噪声HNR分离方法研究

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2、

This paper presented some simulation results of Neural Networks based on the Chebyshev algorithm, its capability is far and away superior to that of BP algorithm and HNR algorithm.

以Chebyshev学习算法为基础,给出了数例神经网络仿真结果,其学习收敛速度大大优于BP算法及HNR算法。

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3、

HNR ( Harmonic to Noise Ratio) reflects the degree of hoarseness voice to a large extent which is one of the main characters to diagnose throat diseases.

谐波和噪声成份的比值(Harmonic to Noise Ratio,HNR)在很大程度上反映了声音的嘶哑程度,是判断喉部疾病的一个主要特征。

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4、

After the surgery, most of the EGG waveform returned to normal, jitter and shimmer decreased and HNR increased, which indicated that the stability of vocal fold vibration improved, CQ, CQP and CIP got smaller additionally.

显微喉镜术后EGG波形多数转为正常,且振动的稳定性提高(jitter和shimmer降低,HNR增加),CQ、CQP和CIP降低。

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