
International Symposium on Chinese Spoken Language Processing
(ISCSLP 2002)
Taipei, Taiwan
August 2324, 2002 

An Improved Entropybased Endpoint Detection Algorithm
Chuan JIA, Bo XU
Chinese Academy of Sciences, Beijing, China
It is found that the detection using basic spectral entropy
becomes difficult and inaccurate when speech signals are
contaminated by high noise. This paper presents an improved
entropybased algorithm. The way to compute spectral
probability density function of entropy is altered by the
introduction of a positive constant. The modification improves
the discriminability between speech and noise and the robustness
of entropy so that it becomes easier to set thresholds. Experiment
results reveal the validity of the improved entropy and prove that
the improved entropy outperforms basic entropy. Moreover, the
improvement of accurate rate (5db SNR) reaches 12.9% for the
detection of start and end points averagely comparing with a
pure energybased algorithm.
Full Paper
Bibliographic reference.
JIA, Chuan / XU, Bo (2002):
"An improved entropybased endpoint detection algorithm",
In ISCSLP 2002, paper 96.