期刊文献+

Speech endpoint detection in low-SNRs environment based on perception spectrogram structure boundary parameter 被引量:9

Speech endpoint detection in low-SNRs environment based on perception spectrogram structure boundary parameter
原文传递
导出
摘要 The Perception Spectrogram Structure Boundary(PSSB)parameter is proposed for speech endpoint detection as a preprocess of speech or speaker recognition.At first a hearing perception speech enhancement is carried out.Then the two-dimensional enhancement is performed upon the sound spectrogram according to the difference between the determinacy distribution characteristic of speech and the random distribution characteristic of noise.Finally a decision for endpoint was made by the PSSB parameter.Experimental results show that,in a low SNR environment from-10 dB to 10 dB,the algorithm proposed in this paper may achieve higher accuracy than the extant endpoint detection algorithms.The detection accuracy of 75.2%can be reached even in the extremely low SNR at-10 dB.Therefore it is suitable for speech endpoint detection in low-SNRs environment. The Perception Spectrogram Structure Boundary(PSSB)parameter is proposed for speech endpoint detection as a preprocess of speech or speaker recognition.At first a hearing perception speech enhancement is carried out.Then the two-dimensional enhancement is performed upon the sound spectrogram according to the difference between the determinacy distribution characteristic of speech and the random distribution characteristic of noise.Finally a decision for endpoint was made by the PSSB parameter.Experimental results show that,in a low SNR environment from-10 dB to 10 dB,the algorithm proposed in this paper may achieve higher accuracy than the extant endpoint detection algorithms.The detection accuracy of 75.2%can be reached even in the extremely low SNR at-10 dB.Therefore it is suitable for speech endpoint detection in low-SNRs environment.
出处 《Chinese Journal of Acoustics》 2014年第4期428-440,共13页 声学学报(英文版)
基金 supported by the National Natural Science Foundation of China.(61071215,61271359,61372146)
  • 相关文献

参考文献1

二级参考文献12

  • 1果永振,何遵文.一种多特征语音端点检测算法及实现[J].通信技术,2003,36(1):8-10. 被引量:8
  • 2Wu G D, Lin C T. Word boundary detection with mel-scale frequency bank in noisy environment. IEEE Transactions on Speech and Audio Processing, 2000; 8(5): 541-554.
  • 3Ramalingam Hariharan et al. Robust end of utterance detection for real-time speech recognition applications. In Proc. ICASSP'2001.
  • 4CHEN Shaoyan et al. A robust method based on likelihood estimation for speech signal detection. International Symposium on Chinese Spoken Language Processing, 2000.
  • 5HUANG Liangsheng et al. A novel approach to robust speech endpoint detection in car environments. International Conference on Acoustics Speech and Signal Processing, 2000.
  • 6Johan de Veth e~ al. Comparison of channel normalization techniques for automatic speech recognition over the phone. Proceedings of the Fourth International Conference on Spoken Language Processing (ICSLP96), 1996; 4:2332-2335.
  • 7Li Qi et al. A Robust real-time endpoint detector with energy normalization for ASR in adverse environments. In Proc. ICASSP'2001, Salt Lake City, 2001.
  • 8Canny J. A computational approach to edge detection.IEEE Transactions on Pattern Analysis and Machine Intelligence, 1986; 8:679-698.
  • 9Petrou M et al. Optimal edge detectors for ramp edge.IEEE Trans on Pattern Analysis and Machine Intelligence, 1991; 13:483-491.
  • 10胡光锐,韦晓东.基于倒谱特征的带噪语音端点检测[J].电子学报,2000,28(10):95-97. 被引量:70

共引文献21

同被引文献53

引证文献9

二级引证文献31

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部