Abstract: In order to solve the problem of using voice signals to accurately identify animals so as to protect and research wild animals. We propose a FCNN (Fully Convolutional Neural Network) combining a fully connected algorithm and a sparse connection algorithm for automatic speech recognition. The fully connected algorithm is used to extract more combined features, and the sparse connection algorithm to select important features to speed up the convergence. The specific model structure and algorithm flow are given, and speech recognition experiments are carried out. The experimental results show that the fully convolutional neural network deep learning algorithm is an effective method for automatic speech recognition. It can solve the problem of frog sound recognition and provide a reference for animal speech recognition.

Key words: speech recognition, convolutional neural network, fully convolutional neural network