A Similarity Measure for Audio Query by Example Based on Perceptual Coding and Compression
Query by example for multimedia signals aims at automatic retrieval of samples from the media database similar to a userprovided example. This paper proposes a similarity measure for query by example of audio signals. The method first represents audio signals using perceptual audio coding and second estimates the similarity of two signals from the advantage gained by compressing the files together in comparison to compressing them individually. Signals which benefit most from compressing together are considered similar. The low bit rate perceptual audio coding preprocessing effectively retains perceptually important features while quantizing the signals so that identical codewords appear, allowing further inter-signal compression. The advantage of the proposed similarity measure is that it is parameter-free, thus it is easy to apply in wide range of tasks. Furthermore, users’ expectations do not affect the results like they do in parameter-laden algorithms. A comparison was made against the other query by example methods and simulation results reveal that the proposed method gives competitive results against the other methods.