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Audio Fingerprint Extraction Using an Adapted Computational Geometry Algorithm

2012· article· en· 3 citations· W2116573767 on OpenAlex· 10.5539/cis.v5n6p88

Why is this work in the frame?

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

Canadian venueIt was published in a Canadian venue.

No Canadian affiliation. An affiliation-only frame — the usual design — would never have seen this work. It is one of the works that make the case for inverting the frame.

The three-model screen

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All three models called this out of scope.

stratum: venue_new · design weight: 2684.25 (the sample is stratified; any rate computed without the weight is wrong)
Claude Opus 4.8OUT
genre: empirical
about Canada: no
confidence: high

Audio fingerprinting algorithm; a signal-processing contribution in its own domain.

GPT-5.6 (high)OUT
genre: empirical
about Canada: no
confidence: high

The work develops an audio fingerprinting algorithm rather than studying research practice.

Grok 4.5OUT
genre: empirical
about Canada: no
confidence: high

Domain CS work on an audio fingerprinting algorithm; object is signal processing, not research practice.

Abstract

This work presents an adapted version of the Computational Geometry Algorithm (CGA) used for the development of audio-based applications and services. The CGA algorithm analyses an audio stream and produces a unique set of points that can be considered to be the audio data “fingerprint”. It is shown that this fingerprint is coding-independent, a fact that can render the proposed algorithm suitable for multiple purposes, including the categorisation of content identity and the identification of audio clips, hence providing support for the realisation of audio sorting/searching tasks and services. Additionally, based on specific novel applications and services, the overall algorithmic performance and efficiency characteristics of the CGA algorithm are discussed and analysed.

Stored with the screening record, where it is evidence for the labels above.

The record

Venue
Computer and Information Science
Topic
Music Technology and Sound Studies
Field
Computer Science
Canadian institutions
Funders
Keywords
Computer scienceFingerprint (computing)Coding (social sciences)AlgorithmSortingSet (abstract data type)Identification (biology)Audio signalSpeech recognitionArtificial intelligenceSpeech coding
Has abstract in OpenAlex
yes