【24h】

Nonlinear Enhancement of Onset for Robust Speech Recognition

机译:语音增强的非线性增强,用于鲁棒语音识别

获取原文

摘要

In this paper we present a novel algorithm called Suppression of Slowly-varying components and the Falling edge of the power envelope (SSF) to enhance spectral features for robust speech recognition, especially in reverberant environments. This algorithm is motivated by the precedence effect and by the modulation frequency characteristics of the human auditory system. We describe two slightly different types of processing that differ in whether or not the falling edges of power trajectories are suppressed using a lowpassed power envelope signal. The SSF algorithms can be implemented for online processing. Speech recognition results show that this algorithm provides especially good robustness in reverberant environments.'
机译:在本文中,我们提出了一种新颖的算法,称为“抑制缓慢变化的分量和功率包络的下降沿”(SSF),以增强频谱特征以实现鲁棒的语音识别,尤其是在混响环境中。该算法受人类听觉系统的优先效应和调制频率特性的影响。我们描述了两种略有不同的处理类型,它们的区别在于使用低通功率包络信号是否抑制了功率轨迹的下降沿。可以将SSF算法实现为在线处理。语音识别结果表明,该算法在混响环境中提供了特别好的鲁棒性。”

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