The invention discloses an acoustic scene identification method based on data enhancement. The method comprises the following steps: firstly, collecting and marking audio samples of different sound scenes; then preprocessing is carried out, and pre-emphasis, framing and windowing processing are carried out on the audio samples; data enhancement is then performed, extracting a harmonic source and an impact source of each audio sample to obtain more sufficient audio samples, extracting logarithmic Mel filter bank characteristics from the audio samples and the harmonic sources and the impact sources of the audio samples, stacking the three characteristics into a three-channel high-dimensional characteristic, and constructing more abundant training samples by adopting a hybrid enhancement technology; and finally, inputting the three-channel high-dimensional features into an Xception network for judgment, and identifying the sound scene corresponding to each audio sample. According to the data enhancement method, the generalization capability of the Xception network classifier can be effectively improved, and the training process of the network is stabilized. When the acoustic scene isidentified, the method can obtain a better identification effect.