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

A technology of energy detection and complex environment, applied in speech analysis, instruments, etc., can solve problems such as lack of pertinence and unsatisfactory effect.

Inactive Publication Date: 2014-01-01
FUZHOU UNIV
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  • Abstract
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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

Method used

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

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Embodiment Construction

[0019] The present invention will be further described below in conjunction with the accompanying drawings and embodiments.

[0020] First of all, in order to allow those skilled in the art to better understand the present invention, a traditional energy detection method is introduced here. Energy detection [7] technology is mostly used for spectrum sensing detection in cognitive radio. This method makes a judgment on whether there is a useful signal by comparing the signal energy within a specific time with the preset decision threshold, without knowing any unknown signal in advance. Prior knowledge, the present invention utilizes this technology to detect the useful birdsong sound signal under the noise environment, and filters the noise frame, and its detection principle is as follows figure 1 shown.

[0021] The noise signal in the present invention is additive noise, and the whole detection process can be regarded as the following binary test hypothesis model problem [8...

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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...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G10L17/26G10L17/02
Inventor 李应张小霞
Owner FUZHOU UNIV
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