Endpoints detection play the important role in speech recognition. But the performance of some often used algorithms will decrease under low SNR conditions. A new concept as distance between autocorrelated functions is brought fully, and a new endpoint detecting method based on it is discussed in this paper. Results from experiment show that this new method has higher performance in endpoint detection. Especially in low SNR circumstance, it still can detect endpoint of speech accurately.
Cite as: Zhu, J., Chen, F.-l. (1999) The analysis and application of a new endpoint detection method based on distance of autocorrelated similarity. Proc. 6th European Conference on Speech Communication and Technology (Eurospeech 1999), 105-108, doi: 10.21437/Eurospeech.1999-30
@inproceedings{zhu99_eurospeech,
author={Jie Zhu and Fei-li Chen},
title={{The analysis and application of a new endpoint detection method based on distance of autocorrelated similarity}},
year=1999,
booktitle={Proc. 6th European Conference on Speech Communication and Technology (Eurospeech 1999)},
pages={105--108},
doi={10.21437/Eurospeech.1999-30}
}