DocumentCode :
2242614
Title :
Based on intelligent voice recognition of forest illegal felling of detecting methods
Author :
Yunjian Tang ; Peng Han ; Zaihuan Wang ; Longcan Hu ; Yue Gao ; Haiyan Li
Author_Institution :
Chongqing Res. Center for Inf. & Autom. Technol., Chongqing, China
fYear :
2012
fDate :
Oct. 30 2012-Nov. 1 2012
Firstpage :
1153
Lastpage :
1156
Abstract :
Note that unlawful cutting of forest becomes more and more rampant at present, and there is no effective solution for real-time detection of such behavior. An approach based on audio recognition was proposed about unlawful cutting of forest. By the analysis of spectral characteristics of the sound signal, and the calculations of similarity value and signal-to-noise ratio in the proposed approach, it can detect whether there is a chainsaw logging behavior. Experimental results show that the proposed method can eliminate interference sound effectively and identify the chainsaw logging sound accurately in real time.
Keywords :
audio signal processing; forestry; interference (signal); law; signal denoising; spectral analysis; audio recognition approach; chainsaw logging behavior; forest illegal felling; intelligent voice recognition; interference sound elimination; real-time detection; signal-to-noise ratio; sound signal spectral characteristics analysis; unlawful forest cutting; Feature extraction; Hidden Markov models; Interference; Satellites; Signal to noise ratio; Speech recognition; Audio recognition; Characteristics analysis; Signal-to-noise ratio; Similarity value;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Cloud Computing and Intelligent Systems (CCIS), 2012 IEEE 2nd International Conference on
Conference_Location :
Hangzhou
Print_ISBN :
978-1-4673-1855-6
Type :
conf
DOI :
10.1109/CCIS.2012.6664564
Filename :
6664564
Link To Document :
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