research-article

Building a personalized audio equalizer interface with transfer learning and active learning

Authors:

Darren GergleAuthors Info & Claims

MIRUM '12: Proceedings of the second international ACM workshop on Music information retrieval with user-centered and multimodal strategies

Pages 13 - 18

https://doi.org/10.1145/2390848.2390852

Published: 02 November 2012 Publication History

Abstract

Potential users of audio production software, such as audio equalizers, may be discouraged by the complexity of the interface and a lack of clear affordances in typical interfaces. In this work, we create a personalized on-screen slider that lets the user manipulate the audio with an equalizer in terms of a descriptive term (e.g. "warm"). The system learns mappings by presenting a sequence of sounds to the user and correlating the gain in each frequency band with the user's preference rating. This method is extended and improved on by incorporating knowledge from a database of prior concepts taught to the system by prior users. This is done with a combination of active learning and simple transfer learning. Results on a study of 35 participants show personalized audio manipulation tool can be built with 10 times fewer interactions than is possible with the baseline approach.

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Cited By

Pepe GGabrielli LSquartini SCattani L(2020)Designing Audio Equalization Filters by Deep Neural NetworksApplied Sciences10.3390/app1007248310:7(2483)Online publication date: 4-Apr-2020
https://doi.org/10.3390/app10072483
Yan RShen FSun CChen X(2020)Knowledge Transfer for Rotary Machine Fault DiagnosisIEEE Sensors Journal10.1109/JSEN.2019.294905720:15(8374-8393)Online publication date: 1-Aug-2020
https://doi.org/10.1109/JSEN.2019.2949057
Goto MDannenberg R(2019)Music Interfaces Based on Automatic Music Signal Analysis: New Ways to Create and Listen to MusicIEEE Signal Processing Magazine10.1109/MSP.2018.287436036:1(74-81)Online publication date: Jan-2019
https://doi.org/10.1109/MSP.2018.2874360
Show More Cited By

Index Terms

Building a personalized audio equalizer interface with transfer learning and active learning
1. Hardware
  1. Communication hardware, interfaces and storage
    1. Signal processing systems
  2. Robustness
    1. Hardware reliability
      1. Signal integrity and noise analysis

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Published In

cover image ACM Conferences

MIRUM '12: Proceedings of the second international ACM workshop on Music information retrieval with user-centered and multimodal strategies

November 2012

82 pages

ISBN:9781450315913

DOI:10.1145/2390848

Program Chairs:
Cynthia C.S. Liem
Delft University of Technology, The Netherlands
,
Meinard Müller
Bonn University & MPI Informatik, Germany
,
Steven K. Tjoa
iZotope, Inc., USA
,
George Tzanetakis
University of Victoria, Canada

Copyright © 2012 ACM.

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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SIGMM: ACM Special Interest Group on Multimedia

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Association for Computing Machinery

New York, NY, United States

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Published: 02 November 2012

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MM '12: ACM Multimedia Conference

November 2, 2012

Nara, Japan

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Cited By

Pepe GGabrielli LSquartini SCattani L(2020)Designing Audio Equalization Filters by Deep Neural NetworksApplied Sciences10.3390/app1007248310:7(2483)Online publication date: 4-Apr-2020
https://doi.org/10.3390/app10072483
Yan RShen FSun CChen X(2020)Knowledge Transfer for Rotary Machine Fault DiagnosisIEEE Sensors Journal10.1109/JSEN.2019.294905720:15(8374-8393)Online publication date: 1-Aug-2020
https://doi.org/10.1109/JSEN.2019.2949057
Goto MDannenberg R(2019)Music Interfaces Based on Automatic Music Signal Analysis: New Ways to Create and Listen to MusicIEEE Signal Processing Magazine10.1109/MSP.2018.287436036:1(74-81)Online publication date: Jan-2019
https://doi.org/10.1109/MSP.2018.2874360
Scott JHua KRui YSteinmetz RHanjalic ANatsev AZhu W(2014)Automated Multi-Track Mixing and Analysis of Instrument MixturesProceedings of the 22nd ACM international conference on Multimedia10.1145/2647868.2654859(651-654)Online publication date: 3-Nov-2014
https://dl.acm.org/doi/10.1145/2647868.2654859
Huang CDuvenaud DArnold KPartridge BOberholtzer JGajos KKuflik TStock OChai JKrüger A(2014)Active learning of intuitive control knobs for synthesizers using gaussian processesProceedings of the 19th international conference on Intelligent User Interfaces10.1145/2557500.2557544(115-124)Online publication date: 24-Feb-2014
https://dl.acm.org/doi/10.1145/2557500.2557544
Percival GBailey NTzanetakis GJaimes ASebe NBoujemaa NGatica-Perez DShamma DWorring MZimmermann R(2013)Physical modelling and supervised training of a virtual string quartetProceedings of the 21st ACM international conference on Multimedia10.1145/2502081.2502101(103-112)Online publication date: 21-Oct-2013
https://dl.acm.org/doi/10.1145/2502081.2502101
Liem CMüeller MTjoa STzanetakis GBabaguchi NAizawa KSmith JSatoh SPlagemann THua XYan R(2012)2nd international ACM workshop on music information retrieval with user-centered and multimodal strategies (MIRUM)Proceedings of the 20th ACM international conference on Multimedia10.1145/2393347.2396541(1509-1510)Online publication date: 29-Oct-2012
https://dl.acm.org/doi/10.1145/2393347.2396541

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