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A Case-Based Reasoning Approach to Plugin Parameter Selection in Vocal Audio Production

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Case-Based Reasoning Research and Development (ICCBR 2022)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 13405))

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Abstract

The field of intelligent systems for music production aims to produce co-creative tools to aid and support musicians’ decision-making while targeting a specific aesthetic in their musical artifact . While case-based reasoning (CBR) approaches have been used to assist music generation and recommendation, music production has not yet been explored. This paper proposes using CBR within a co-creative agent to assist musicians in their aesthetic goals through a vocal audio plugin. Results show that although participants were interested in using a co-creative agent throughout the production process, they acted against the vocal plugin parameter recommendations set by the agent. Participants showed frustration when the co-creative agent acted in a way that deviated from set expectations. From this research, we posit that explainability is an essential aspect of effective CBR models within co-creative agents.

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Notes

  1. 1.

    https://www.ableton.com/en/live/.

  2. 2.

    https://cycling74.com/products/max.

  3. 3.

    https://www.maxforlive.com/library/device/6346/poundcake-compressor.

  4. 4.

    https://www.ableton.com/en/packs/creative-extensions/.

  5. 5.

    https://maxforlive.com/library/device/5768/gmaudio-dynamic-eq.

  6. 6.

    https://www.ableton.com/en/packs/convolution-reverb/.

  7. 7.

    https://www.noiiz.com.

  8. 8.

    https://otter.ai.

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Author information

Authors and Affiliations

  1. University of Utah, Salt Lake City, UT, 84105, USA

    Michael Clemens, Nancy N. Blackburn, Rushit Sanghrajka, Monthir Ali, M. Gardone, Shilpa Thomas, Hunter Finney & Rogelio E. Cardona-Rivera

Authors
  1. Michael Clemens
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  2. Nancy N. Blackburn
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  3. Rushit Sanghrajka
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  4. Monthir Ali
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  5. M. Gardone
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  6. Shilpa Thomas
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  7. Hunter Finney
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  8. Rogelio E. Cardona-Rivera
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Corresponding author

Correspondence to Michael Clemens .

Editor information

Editors and Affiliations

  1. University College Dublin, Dublin, Ireland

    Mark T. Keane

  2. The Robert Gordon University, Aberdeen, UK

    Nirmalie Wiratunga

6Appendix: Interview Questions Guide

6Appendix: Interview Questions Guide

1.1 6.1Overall Experience

  • Please upload your output file (download and test this, please)

  • Would you describe your workflow while completing the experiment?

  • How was your overall experience with the plugin?

1.2 6.2Experiment Questions (Plugin/Co-creative Agent)

  • How did you feel about the different tracks you worked with?

  • Were you aware of the updated presets that occurred after the third track? (IF NOT: explain the process, then ask these questions:)

  • How did it affect your workflow? (easier, quicker, recommendation, co-creative)

  • In what ways did you find the plugin helpful?

  • In what ways was the plugin a hindrance?

  • What was your favorite part about the plugin’s design?

  • What was your least favorite part about the plugin’s design?

  • What would you change about the plugin design if you could? (optional)

  • Would you add or remove any pieces of the plugin for producing a vocal mix? If yes, why?

1.3 6.3Demographics

  • How long have you been producing music?

  • What is your favorite Digital Audio Workstation (DAW) to produce with?

  • How familiar are you with Ableton Live? How long have you used it?

  • Have you used AI-based mastering tools such as Landr, Dolby.io, or SoundCloud before in your mixing/mastering process?

  • Have you used machine learning (ML) tools such as Magenta in your creative process?

  • Do you have any plugins that you use regularly and why?

  • Do you tend to use stock presets when using plugins, or do you modify them and create your own?

  • Have you used an adaptive plugin before? If so, which one(s)?

  • How was your experience with them?

1.4 6.4Wrap-Up

  • Is there anything I covered that you would like to revisit or anything that I missed that you would like to add?

  • What is your address for your gift card?

  • Those are all the questions we have for you. Thanks for your participation.

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Clemens, M. et al. (2022). A Case-Based Reasoning Approach to Plugin Parameter Selection in Vocal Audio Production. In: Keane, M.T., Wiratunga, N. (eds) Case-Based Reasoning Research and Development. ICCBR 2022. Lecture Notes in Computer Science(), vol 13405. Springer, Cham. https://doi.org/10.1007/978-3-031-14923-8_23

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  • DOI: https://doi.org/10.1007/978-3-031-14923-8_23

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-14922-1

  • Online ISBN: 978-3-031-14923-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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