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Music-information retrieval in environments containing acoustic noise

Published: 03 November 2014 Publication History

Abstract

In the field of Music-Information Retrieval (Music-IR), algorithms are used to analyze musical signals and estimate high-level features such as tempi and beat locations. These features can then be used in tasks to enhance the experience of listening to music. Most conventional Music-IR algorithms are trained and evaluated on audio that is taken directly from professional recordings with little acoustic noise. However, humans often listen to music in noisy environments, such as dance clubs, crowded bars, and outdoor concert venues. Music-IR algorithms that could function accurately even in these environments would therefore be able to reliably process more of the audio that humans hear. In this paper, I propose methods to perform Music-IR tasks on music that has been contaminated by acoustic noise. These methods incorporate algorithms such as Probabilistic Latent Component Analysis (PLCA) and Harmonic-Percussive Source Separation (HPSS) in order to identify important elements of the noisy musical signal. As an example, a noise-robust beat tracker utilizing these techniques is described.

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cover image ACM Conferences
MM '14: Proceedings of the 22nd ACM international conference on Multimedia
November 2014
1310 pages
ISBN:9781450330633
DOI:10.1145/2647868
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Publication History

Published: 03 November 2014

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Author Tags

  1. acoustic noise
  2. music
  3. music-information retrieval

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MM '14
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MM '14: 2014 ACM Multimedia Conference
November 3 - 7, 2014
Florida, Orlando, USA

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MM '14 Paper Acceptance Rate 55 of 286 submissions, 19%;
Overall Acceptance Rate 2,145 of 8,556 submissions, 25%

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