Birdsong automatic identification method based on feature fusion

Abstract

The invention discloses a birdsong automatic identification method based on feature fusion, and belongs to the technical field of ecological monitoring and acoustic signal identification. The method comprises the following steps: firstly, collecting different birdsongs, each birdsong including a plurality of birdsong segment; then, extracting frequency domain features of each birdsong segment; then, extracting image domain features of each birdsong segment; then, splicing the frequency domain features and the image domain features extracted from each birdsong segment correspondingly in a one-to-one manner, to form a high-dimensional feature set of multi-feature elements; secondly, selecting features of the high-dimensional feature set of multi-feature elements, to obtain a low-dimensionalfeature set of multi-feature elements; finally, identifying bird species by combining the low-dimensional feature set with a classifier. The method effectively overcomes shortcomings that a single feature is difficult to describe birdsong audio characteristics, the method has strong anti-background noise interference ability, low calculation complexity, short running time, and reliable data and iseasy to implement.

Description

technical field [0001] The invention belongs to the technical field of ecological monitoring and acoustic signal recognition, in particular to an automatic bird song recognition method based on feature fusion. Background technique [0002] With many species on the verge of extinction due to habitat loss and climate change, biodiversity monitoring and assessment has become a far-reaching and challenging global issue. With the widespread use of sound recording sensors, acoustic monitoring has become an effective means of biodiversity monitoring. Among them, birds, as an environmental indicator organism, are ideal indicators for ecological acoustic monitoring. The detection and automatic recognition of birdsong in acoustic monitoring data in natural environments is an important part of ecological research. [0003] Among them, the bird song recognition process is mainly to extract features for bird song clips, and then input them into a specific classifier to obtain bird spec...

AI Technical Summary

Problems solved by technology

Both of them extract a single feature for bird song recognition, but it is difficult for a single feature to completely describe all the audio characteristics of a bird song segment, and when multiple features are simply spliced ​​to obtain high-dimensional features, they often face the problem of "dimension disaster".

[0004] It can be seen that there are defects such as incomplete methods and single functions in the prior art.

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