Open AccessDOI
An industrial-strength audio search algorithm
Avery Li-Chun Wang
- pp 582-588
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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
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Multifaceted Approaches to Music Information Retrieval
TL;DR: This thesis proposes a novel prototypical system which explicitly solicits the intended narrative for the video, and employs information from collaborative web resources to establish connotative connections to musical descriptors, followed by audiovisual reranking.
Journal ArticleDOI
High performance indexing for massive audio fingerprint data
TL;DR: A hybrid data structure which combines linked list with vector to store the values in the hash table to balance the searching performance and the memory usage is designed and evaluated.
Journal ArticleDOI
Landmark-based music recognition system optimisation using genetic algorithms
TL;DR: The whole optimisation process of a Landmark-based Music Recognition System using genetic algorithms is described, which defines the actual structure of the algorithm as a chromosome by transforming its high relevant parameters into various genes and building up an appropriate fitness evaluation method.
Book ChapterDOI
Smart Audio Sensing‐Based HVAC Monitoring
TL;DR: This chapter proposes a Smart Audio SEnsing‐based Maintenance (SASEM) system that has a single unifying intellectual focus, that is, enabling predictive maintenance of building equipment by autonomously monitoring and analyzing their acoustic emissions.
Proceedings ArticleDOI
Content-Based Multimedia Copy Detection
TL;DR: A two-step search based on a clustering technique and a lookup table that reduces the number of comparisons between the query and the reference fingerprints is proposed to accelerate the search of fingerprints by using a Graphics Processing Unit (GPU).
References
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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.