Bird Songs Recognition Based on Ensemble Extreme Learning Machine

Abstract

ELM (Extreme Learning Machine) is a random method for Single-hidden layer feedforward neural network construction, and MFCC (Mel-frequency Cepstrum Coefficient) is a kind of feature parameter for speech recognition. Based on Ensemble ELM research on bird songs recognition technology, this paper firstly preprocesses the bird songs data collected by web crawler, then extracts MFCC feature parameters from the songs data, and gets the improved MFCC feature parameters through differential calculation. Finally, Ensemble ELM is used for bird songs classification and recognition. The experimental results show that the Ensemble ELM method can achieve a recognition rate of 90.42% in the classification of 10 kinds of birds.