Digital Audio Fingerprinting, Audio Identification, Music Recognition, Broadcast Monitoring, Copyright Protection, Audio Analysis, Shazam, Content-Based Audio Retrieval
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Abstract
Digital audio fingerprinting is a technology used to identify and analyze audio content by creating a unique digital signature. It has various applications including music identification, broadcast monitoring, and copyright protection.
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[...] (2015). Song Recognition Using Audio Fingerprinting. University of Rochester, Department of Electrical and Computer Engineering. - Cano, P., Batlle, E., Gómez, E., Gomes, L. C. T., & Bonnet, M. (2003). Audio Fingerprinting: Concepts and Applications. Studies in Computational Intelligence (SCI) 233-245. Springer. [...]
[...] The use cases of digital audio fingerprinting are diverse and rapidly expanding. One of the most important applications is music identification, where systems like Shazam allow users to identify songs by recording a brief audio excerpt in noisy and real-world environments. These systems extract a digital fingerprint from the recorded audio and compare it to a vast database, enabling the user to discover the song title, artist, and album in real-time (Khatri et al., 2015). This process not only involves identifying the song, but also synchronizing the audio fingerprint with the corresponding metadata, regardless of the playback speed or ambient noise (Cano et al., 2005). [...]
[...] Finally, the use of digital audio fingerprinting also concerns the general public, either through mobile applications that have access to the context or metadata of a song being played. Some services allow users to receive artist biographies, lyrics or information about a concert by simply recording an audio excerpt (Khatri et al., 2015). Bibliography - Cano, P., & Batlle, E. (2005). A Review of Audio Fingerprinting. Journal of VLSI Signal Processing, 271-284. Springer. - Khatri, V., Dillingham, L., & Chen, Z. [...]
[...] A number of key properties ensure the effectiveness and versatility of digital audio fingerprinting systems. First, robustness. The digital fingerprint must retain its coherence despite common distortions such as compression, background noise, sampling frequency changes, and transmission interference. This ensures that the digital fingerprint will be able to identify the audio even if the original signal has been modified or degraded by encoding formats such as MP3 or GSM (Batlle et al., 2003). Another crucial property is adaptability. The system must be able to correctly identify the audio content while limiting error rates. [...]
