Open AccessDOI
An industrial-strength audio search algorithm
Avery Li-Chun Wang
- pp 582-588
Reads0
Chats0
TLDR
In this article, the authors developed and commercially deployed a flexible audio search engine that is noise and distortion resistant, computationally efficient, and massively scalable, capable of quickly identifying a short segment of music captured through a cellphone microphone in the presence of foreground voices and other dominant noise, and through voice codec compression.Abstract:
We have developed and commercially deployed a flexible audio search engine. The algorithm is noise and distortion resistant, computationally efficient, and massively scalable, capable of quickly identifying a short segment of music captured through a cellphone microphone in the presence of foreground voices and other dominant noise, and through voice codec compression, out of a database of over a million tracks. The algorithm uses a combinatorially hashed time-frequency constellation analysis of the audio, yielding unusual properties such as transparency, in which multiple tracks mixed together may each be identified. Furthermore, for applications such as radio monitoring, search times on the order of a few milliseconds per query are attained, even on a massive music database.read more
Citations
More filters
Proceedings ArticleDOI
A novel way of identifying suspect picture files
R.J. Shaw,A.S. Atkins +1 more
TL;DR: A novel approach is proposed by converting the suspect picture file to a sound file, generating a `fingerprint' for this sound wave and using a matching algorithm to identify the file from a suspect file database.
Dissertation
Laboratory assignments for teaching introductory signal processing concepts
TL;DR: This thesis proposes labs for a new, applications-based signal processing class and will combine signal processing techniques with computational tools to improve student understanding of signal processing concepts and show them the power of signalprocessing in everyday applications.
Journal Article
Alignment and Timeline Construction for Incomplete Analogue Audience Recordings of Historical Live Music Concerts
TL;DR: This paper proposes a method to align multiple digitised analogue recordings of same concerts of varying quality and song segmentations, and evaluates alignment methods on a synthetic dataset and applies the algorithm to real-world data.
Extrema features for global-localization and pattern matching of time-series data
TL;DR: This dissertation describes the use of extrema features for the purposes of localization and pattern matching in time-series data and develops a wavelet-based framework to extract extreMA features from raw data.
Teli̇f haklari i̇daresi̇ne yöneli̇k müzi̇k taki̇p si̇stemi̇: müzi̇ği̇n geometri̇k beti̇mlemesi̇ musi̇c t racking system for royalty ri̇ghts management: geometri̇cal representation of musi̇c
Erdem Ü,Cemil Demir +1 more
TL;DR: Studies for to the project named "Music Tracking System for Royalty Rights Management" funded by the TUBITAK ARDEB 3501 grant program are presented and technical details about the performance of the system is shown.
References
More filters
Journal ArticleDOI
Content-based classification, search, and retrieval of audio
TL;DR: The audio analysis, search, and classification engine described here reduces sounds to perceptual and acoustical features, which lets users search or retrieve sounds by any one feature or a combination of them, by specifying previously learned classes based on these features.
Proceedings Article
A Highly Robust Audio Fingerprinting System.
Jaap A. Haitsma,Ton Kalker +1 more
TL;DR: An audio fingerprinting system that uses the fingerprint of an unknown audio clip as a query on a fingerprint database, which contains the fingerprints of a large library of songs, the audio clip can be identified.
Proceedings ArticleDOI
MACS: music audio characteristic sequence indexing for similarity retrieval
TL;DR: The algorithm tries to capture the intuitive notion of similarity perceived by humans: two pieces are similar if they are fully or partially based on the same score, even if they were performed by different people or at different speed.