Speech endpoint detection is an important part of speech processing and recognition.Traditional endpoint detection methods have low accuracy in speech endpoint detection and poor anti-noise ability under the condition of low signal-to-noise ratio
In this paper
an improved zero-entropy feature parameter speech endpoint detection algorithm is proposed.This method studies the short-time zero-crossing rate
short-time energy and basic spectral entropy of three speech endpoint detection feature parameters
and proposes a new speech parameter
namely
the short-time energy zero-entropy value. Finally
a two-threshold algorithm is adopted to carry out endpoint detection.Simulation results show that compared with the traditional zero-energy ratio endpoint detection method
this method has higher endpoint detection accuracy under different low SNR conditions.
WU B F, WANG K C. Robust endpoint detection algorithm based on the adaptive band-partitioningspectral entropyin adverse environments[J]. IEEE Transactions on Speech and Audio Processing, 2005, 13(5):762-775. DOI: 762
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