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Proceedings ArticleDOI

Scalable and robust audio fingerprinting method tolerable to time-stretching

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TLDR
The experiment results show the method is highly tolerable to time-stretch than the state-of-the-art Shazam's audio fingerprinting, and is scalable and tolerant toTime-stretching.
Abstract
A time-stretching invariant, robust audio fingerprinting method, based on landmarks in the audio spectrogram is proposed in this paper. Time-stretching of audio clips or songs are done to evade copyright detection as most of the fingerprinting techniques are time dependent. Time-stretching is also used in music industry to produce remix & song mash-ups and in multimedia broadcasting to fit content within the required duration. The proposed algorithm is based on the audio hashing of frequency peaks in the spectrogram. It is scalable and tolerant to time-stretching. The experiment results show the method is highly tolerable to time-stretch than the state-of-the-art Shazam's audio fingerprinting.

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Journal ArticleDOI

Pattern analysis based acoustic signal processing: a survey of the state-of-art

TL;DR: The aim of this state-of-art paper is to produce a summary and guidelines for using the broadly used methods, to identify the challenges as well as future research directions of acoustic signal processing.
Journal ArticleDOI

Robust and efficient multiple alignment of unsynchronized meeting recordings

TL;DR: This paper proposes a way to generate a single high-quality audio recording of a meeting using no equipment other than participants' personal devices using an adaptive audio fingerprint based on spectrotemporal eigenfilters, where the fingerprint design is learned on-the-fly in a totally unsupervised way to perform well on the data at hand.
Journal ArticleDOI

Known-Artist Live Song Identification Using Audio Hashprints

TL;DR: This paper proposes a multistep approach to address the problem of live song identification for popular bands by representing the audio as a sequence of binary codes called hashprints, derived from a set of spectrotemporal filters that are learned in an unsupervised artist-specific manner.
Proceedings ArticleDOI

Audio fingerprint parameterization for multimedia advertising identification

TL;DR: This study suggests a set of parameterization steps which could be successfully implemented in other related audio applications and shows an accuracy of 99% using three seconds of granularity samples, and also the best compromise between processing time and performance is achieved.
References
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Journal ArticleDOI

Automatic detection of known advertisements in radio broadcast with data-driven ALISP transcriptions

TL;DR: An audio indexing system to search for known advertisements in radio broadcast streams, using automatically acquired segmental units called ALISP units, which achieve a mean precision of 95% with the corresponding recall value of 97%.
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