Voice Activity Detection Based on the Improved Dual-Threshold Method

Voice activity detection of speech signal is an important part in the process of speech recognition. The accuracy of voice activity detection is directly related to the accuracy of speech recognition. In this paper, the use of locomotive voice as test data, using the traditional dual-threshold method for voice activity detection. It is found that under the quiet and noisy conditions the traditional dual-threshold method obtained information of speech voice activity detection having lots of errors. In view of the above problems, this paper presented an improved dual-threshold method to make voice activity detection, processing speech signal, short-time average energy and zero crossing rate. And through MATLAB simulation, the experimental results show that under the quiet and noisy conditions comparing the improved method proposed by this paper and the traditional method, are closer to real speech voice activity part in the test data.