In order to solve the problem of large amount of data and slow retrieval speed in the existing audio retrieval, a fixed audio retrieval method is proposed in this study based on compressed sensing and audio fingerprint dimensionality reduction. In the training stage of audio retrieval, the sample audio signal is sparse processed, and the sparse audio data is compressed by the compression sensing algorithm, then the audio fingerprint is extracted, and then the audio fingerprint discrete Gini coefficient is introduced to reduce the dimension of the fingerprint by calculating the discrete Gini coefficient of each dimension of the audio fingerprint. In the recognition stage of audio retrieval, we use the same algorithm as in the training stage to process the audio to be tested and match with the sample audio fingerprint. The experimental results show that the proposed audio retrieval method greatly reduces the storage of the sample audio database and improves the audio retrieval speed on the basis of ensuring a better retrieval accuracy.