Audio fingerprint extraction, Shazam algorithm, music identification, signal filtering, frequency transformation, acoustic features, hashing, database searching
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This document explains the process of generating a digital fingerprint for audio signals, specifically the steps involved in Shazam's music identification algorithm, including filtering, frequency transformation, and searching.
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[...] Springer Science & Business Media. SCHÖN, T. B., & LINDE, T. (2008). System identification techniques using particle filters. Automatica, vol no p. 605-616. GUPTA, A., & BHOWMICK, S. (2019). Signal-to-noise ratio analysis in real-time systems. IEEE Signal Processing Letters, vol no p. 500-504. HAUG, E. J. [...]
[...] This phenomenon, very frustrating, was a great source of discontent for many music enthusiasts. The feeling of being unable to associate a song or a captivating musical piece or memorable lyrics to a specific artist or title could leave a sense of incompleteness. All the more so since sometimes pieces can be associated with memories. This feeling can be compared to that felt when one forgets the relevant idea that was on their mind. For these music-loving listeners or just curious ones, hearing a memorable piece but not being able to find it meant often missing the opportunity to listen to it again or to integrate it into their music collection. [...]
[...] Robust system identification methods for noisy environments. Signal Processing Journal, vol no p. 421-431. DORBERG, R. (2019). Advances in identification of hybrid dynamical systems. Nonlinear Dynamics, vol no p. 223-240. LIU, T., & ZHENG, X. (2014). Multi-resolution analysis in audio fingerprinting algorithms. Digital Signal Processing, vol p. 113-122. LEE, J. [...]
[...] This is due to the fact that the filtering operation is quite complicated. It is sufficient to implement eighty percent of the filtering that yields eighty percent of the results. This also allows for the passage time through the filter cascade (WANG, A. L.-C.). Figure Impact of filtering on the extraction of the digital fingerprint This filtering is primarily used to isolate relevant information by eliminating unwanted components that can hinder identification. There are several types of filters commonly used in this context: low-pass filters, which remove unwanted high frequencies; high-pass filters, to attenuate non-relevant low frequencies; and band-pass filters, which select a frequency range where useful information is concentrated. [...]
[...] It is not simply a matter of brute computing power, but also of fine-tuning the underlying processes, such as fingerprint hashing, indexing, and database management. In fact, optimization corresponds to drastically reducing the calculation time. In fact, the Shazam application uses a musical piece of around seconds as input data. In a five-minute musical piece, several intervals of lengths exist It's not just the ratio between the five minutes and the 5 seconds: 300 seconds divided by which is 60. In fact, the initial second allows defining the data interval. [...]
