The invention discloses a convolutional neural network-based music signal multi-instrument identification method. The method comprises the following steps of S1, extracting two features from an inputaudio, wherein the two features comprise a pitch feature matrix and a constant Q transformation matrix based on tone; S2, carrying out classification according to musical instrument groups, includingtubes, strings and percussion music, inputting the constant Q transformation matrix into a primary convolutional neural network to obtain a classification matrix, and inputting the classification matrix into a classifier to obtain a coarse classification result, namely the musical instrument group type; and S3, on the basis of the classification matrix, inputting the classification matrix into a secondary convolutional neural network with an attention network in combination with a pitch matrix to obtain a subdivision result, namely a specific musical instrument, wherein the attention network allocates weights to different harmonic waves. The method is suitable for musical instrument identification tasks in music information retrieval and can be used for the musical instrument identification method in music automatic transcription.