The invention discloses an LSTM and SAE-based telephone voice emotion analysis and recognition method; according to the method, voice information is subjected to a series of preprocessing of sampling,quantifying, pre-emphasis, framing, windowing and the like, and then fast fourier transformation is carried out on the voice information to obtain frequency domain characteristics of the voice information, and next, the voice characteristic parameters MFCC are extracted. By adoption of the method, an LSTM+ SAE neural network model is established to train the extracted MFCC characteristic parameters to obtain depth characteristic information of voice signals; the classification accuracy is obtained by combining a full-connection layer and a softmax regression algorithm, and model training is completed; and finally, the MFCC characteristic parameters to be tested are input into a trained model, emotion analysis is carried out on the telephone voice, and the emotion of a speaker is judged.