On audio recognition performance via robust hashing

In recent years, automated audio recognition is arising as a relevant issue. One of the most successful approaches has proved to be the Philips method [1], by Haitsma et al.. Our work exploits this framework in order to allow for a better tuning of the algorithm. In particular, we show that more accurate hashes do not always lead to a better performance, which can then be attained with an inferior computational cost. A simple and efficient search method is also proposed.