【24h】

Low SNR Robust Chinese Tone Extraction Based Human Adititory Model

机译:低信噪比鲁棒中文音提取的人称性模型

获取原文

摘要

This paper proposes a robust Chinese tone extraction algorithm based on the human auditory mechanism and short-term stationary of Chinese speech. In this method, we use the pooledcorrelogram based on human auditory model to extract the pitch of speech. An unsupervised lateral inhibitory network is used to get the peak position, which simulates the lateral inhibitory phenomenon in human auditory system. The pitch restricition between successive frames of speech is imposed to get rid of miscarriage of justice in the output of lateral inhibitory network. As shown in the experiments, the method can extract Chinese tone quite well even in rather low SNR cases. It can separate the individual tone clearly as two speakers talk simultaneously.
机译:提出了一种基于人类听觉机制和汉语语音短期平稳性的鲁棒汉语语音提取算法。在这种方法中,我们使用基于人类听觉模型的合并相关图来提取语音音调。使用无监督的侧向抑制网络来获取峰位置,该峰位置模拟了人类听觉系统中的侧向抑制现象。连续语音框架之间的音高限制被施加,以消除横向抑制网络输出中的误判。如实验所示,即使在信噪比较低的情况下,该方法也可以很好地提取中文音。当两个说话者同时讲话时,它可以清楚地将单个音调分开。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号