Even though the methods are intended for generic audio similarity, it is likely that as such they are restricted only to relatively low-level similarities.
We also present approximations for the Kullback-Leibler divergence between GMMs, which have not been previously used in audio similarity measurement.
The SOM-enhanced JukeBox, proposed by Rauber et al. [8] automatically creates an organization of music archives based on audio similarity.
Several authors have presented systems that estimate the audio similarity of two pieces of music through the calculation of a distance metric, such as the Euclidean distance, between spectral features calculated from the audio, related to the timbre or pitch of the signal.
First, the audio signal similarity is calculated with the Psim function, which avoids the equidistance.
A second sound (sound 2) was noted on the emergency recording, which, according to the audio expert, showed similarities to sound 1.
The fundamental problem when measuring the similarity between audio samples is the imperfect definition of similarity.
This approach is based on finding self-similarities among audio features.
We observe that the similarity of audio signals can be measured by the difference between the probability density functions (pdfs) of their frame-wise features.
This paper focuses on reducing the transmission (and storage) requirements of spot microphone signals (before those are mixed into the final multichannel audio mix), by exploiting the similarities between such signals of the same multimicrophone recording.
