Twitter identification method based on self-adaption energy detection under complex environment

Abstract

The invention relates to a twitter identification method based on self-adaption energy detection under a complex environment. The method is characterized by comprising the following steps of firstly, dividing twitter into three frequency bands according to the frequency distribution condition of the twitter; secondly, detecting twitter acoustical signals containing noise through a self-adaption energy detection method based on noise power spectrum estimation and the foreground sound existence probability, and screening out the useful twitter signals; thirdly, extracting Mel-scale WPSCC features from the useful twitter signals according to distribution of the Mel scales; fourthly, conducting modeling, classification and identification on the extracted Mel-scale WPSCC features and extracted Mel-scale MFCC features through an SVM classifier. The WPSCC features extracted through the method have a better anti-noise function and are better in identification performance after undergoing self-adaption energy detection, the method is more suitable for twitter identification under the complex environment and has a good classification and identification effect on the twitter sound containing noise under the complex environment.

Description

technical field [0001] The invention relates to the technical field of bird song recognition, in particular to a bird song recognition method based on adaptive energy detection in a complex environment. Background technique [0002] Birds in a complex ecological environment can make a variety of calls, and their sounds contain rich information that is closely related to the living environment of humans. People can obtain relevant bird information by detecting, analyzing and identifying bird sounds, understand the number, type and living habits of bird species populations, monitor and protect birds, and evaluate the surrounding ecological environment or living environment and forecast. [0003] With the development of science and technology, many research results have been obtained in the classification and recognition technology of bird sounds. Literature [1] used sinusoidal curves to model the syllables of continuous bird calls, and then used the obtained parameters to cl...

AI Technical Summary

Problems solved by technology

The traditional endpoint detection method, such as the double-threshold method of short-term energy and zero-crossing rate, works better in the case of no noise, but in the complex noise environment, its effect is not ideal.

Therefore, the energy detection method is introduced, but the traditional energy detection method requires prior knowledge of noise and is not targeted

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