JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE) ›› 2016, Vol. 46 ›› Issue (2): 57-63.doi: 10.6040/j.issn.1672-3961.2.2015.147

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An endpoint detection algorithm based on frequency-domain characteristics and transition fragment judgment

GUO Yu, ZHANG Erhua*, LIU Chi   

  1. School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing 210094, Jiangsu, China
  • Received:2015-05-12 Online:2016-04-20 Published:2015-05-12

Abstract: In order to improve the accuracy of speech endpoint detection as well as enhance robustness of the endpoint detection algorithm in noisy environment, two new endpoint detection parameters were proposed. The spectrum entropy based on critical band took both perceptual characteristics of the human auditory system and the differences between speech and noise signals in frequency domain distribution into account, as well as the minus frequency-domain energy parameter paid attention to the difference between speech frames and silence frames in frequency energy. The advantages of those two parameters were combined to constitute a robust endpoint detection parameter. Meanwhile, in order to avoid the miscarriage of judgment caused by the unitary threshold, the transition fragment judgment based on statistics of characteristics distribution was applied. The experiment results showed that the endpoint detection algorithm had better discrimination for speech frames and silence frames, the algorithm could carry out better accuracy than other conventional anti-noisy endpoint detection algorithms under different and low signal-to-noise ratio noisy environments, especially in the case of non-stationary noise, the accuracy improved by more than 5%.

Key words: transition fragment judgment, energy entropy, frequency-domain energy, critical band, endpoint detection, spectrum entropy

CLC Number: 

  • TP391.42
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