• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>IEEE transactions on audio, speech and language processing >A quantitative assessment of group delay methods for identifying glottal closures in voiced speech
【24h】

A quantitative assessment of group delay methods for identifying glottal closures in voiced speech

机译：语音识别中声门闭合的群时延方法的定量评估

获取原文
获取原文并翻译 | 示例
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

Measures based on the group delay of the LPC residual have been used by a number of authors to identify the time instants of glottal closure in voiced speech. In this paper, we discuss the theoretical properties of three such measures and we also present a new measure having useful properties. We give a quantitative assessment of each measure's ability to detect glottal closure instants evaluated using a speech database that includes a direct measurement of glottal activity from a Laryngograph/EGG signal. We find that when using a fixed-length analysis window, the best measures can detect the instant of glottal closure in 97% of larynx cycles with a standard deviation of 0.6 ms and that in 9% of these cycles an additional excitation instant is found that normally corresponds to glottal opening. We show that some improvement in detection rate may be obtained if the analysis window length is adapted to the speech pitch. If the measures are applied to the preemphasized speech instead of to the LPC residual, we find that the timing accuracy worsens but the detection rate improves slightly. We assess the computational cost of evaluating the measures and we present new recursive algorithms that give a substantial reduction in computation in all cases.
机译：许多作者已经使用了基于LPC残差群延迟的方法来确定浊音中声门关闭的时刻。在本文中，我们讨论了三种此类措施的理论性质，并且还提出了一种具有有用性质的新措施。我们对使用语音数据库（包括直接从喉镜/ EGG信号直接测量声门活动）评估的声门闭合瞬间进行检测的每项措施的能力进行定量评估。我们发现，当使用固定长度的分析窗口时，最好的措施可以在97％的喉循环中检测到声门关闭的瞬间，标准偏差为0.6 ms，并且在这些循环的9％中，还发现了一个额外的激励瞬间。通常对应声门开口。我们表明，如果分析窗口的长度适合语音音调，则可以提高检测率。如果将这些措施应用于预加重语音而不是LPC残差，我们会发现定时精度变差了，但检测率却略有提高。我们评估了评估这些措施的计算成本，并提出了新的递归算法，这些算法在所有情况下都大大减少了计算量。

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