In future mobile communication system, it is very important to expand the limited radio resources through exploiting the silence compression technology In this paper, a new speech classifier based on YinYang Compensatory soft computing theory is described. The classifier is used to divide the noisy speech signal input to the mobile phone into the active speech (including voiced, unvoiced and transition) and inactive speech (including silence or noise) during conversation. The novel speech classifier algorithm is discussed and verified at the GSM discontinuous transmission platform with an adaptive multi-rate speech codec. We found the accuracy of the classifier is approximately 98% in clean background acoustic environment. Moreover, we analyzed its classification accuracy in eight types of noise environment with varying signal-to noise ratio.
Cite as: Chen, D., Kuang, J., Zhang, Y. (2000) A new speech classifier based on Yinyang compensatory soft computing theory. Proc. 6th International Conference on Spoken Language Processing (ICSLP 2000), vol. 2, 186-189, doi: 10.21437/ICSLP.2000-240
@inproceedings{chen00f_icslp,
author={Dong Chen and Jingming Kuang and Yan Zhang},
title={{A new speech classifier based on Yinyang compensatory soft computing theory}},
year=2000,
booktitle={Proc. 6th International Conference on Spoken Language Processing (ICSLP 2000)},
pages={vol. 2, 186-189},
doi={10.21437/ICSLP.2000-240}
}