A Speech Endpoint Detection Algorithm Based on Entropy and RBF Neural Network

  title={A Speech Endpoint Detection Algorithm Based on Entropy and RBF Neural Network},
  author={Xueying Zhang and Gaoyun Li and Feng Qiao},
  journal={2007 IEEE International Conference on Granular Computing (GRC 2007)},
Speech endpoint detection is an important step in the field of speech analysis, speech synthesis and speech recognition. This paper proposed an endpoint detection algorithm, which used amplitude entropy, spectral entropy and frame energy as feature parameters and utilized RBF neural network as a feature classification system. 170 sentences are used as testing data to detect speech endpoint, which length is from 4 second to 7 second. The experiments show that the testing results using RBF neural… CONTINUE READING
2 Citations
4 References
Similar Papers


Publications citing this paper.


Publications referenced by this paper.
Showing 1-4 of 4 references

A novel approach to entropy-based endpoint detection of noise speech

  • Jianfeng Yan, Yuzhuo Fu
  • Computer Simulation, Vol.22,
  • 2005
1 Excerpt

A survey of endpoint detection methods for speech signal

  • Shengyue Yang, Yanyu Zhou, Shenxi Huang
  • Information technology,
  • 2005
1 Excerpt

A scheme of speech endpoint detection based on information entropy

  • Sigen Chen, Yingmin He
  • Applied Science and Technology, Vol.28,
  • 2001

Similar Papers

Loading similar papers…