Content-based signatures are designed to be a robust bitstream representation of the content so as to enable content identi cation even though the original content may go through various signal processing operations. In this paper, we propose a novel content-based audio signature extraction method that captures temporal evolution of the audio spectrum. The proposed method, rst, divides the input audio into overlapping chunks and computes a spectrogram for each chunk. Then, it projects each of the spectrograms onto random basis vectors to create a signature that is a low-dimensional bitstream representation of the corresponding spectrogram. Our experimental results show the robustness and sensitivity of the proposed content-based audio signature extraction method for various signal processing operations on audio content.