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Considerations for Developing Sound in Golf Putting Experiments

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Music Technology with Swing (CMMR 2017)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 11265))

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Abstract

This chapter presents the core interests and challenges of using sound for learning motor skills and describes the development of sonification techniques for three separate golf-putting experiments. These studies are part of the ANR SoniMove project, which aims to develop new Human Machine Interfaces (HMI) that provide gestural control of sound in the areas of sports and music. After a brief introduction to sonification and sound-movement studies, the following addresses the ideas and sound synthesis techniques developed for each experiment.

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Notes

  1. 1.

    In this context sound is defined as any non-verbal audio. Defining sonification is a bit of a controversial topic, especially in recent years, as some composers and sound artists make sound through the manipulation of values from data streams and large databases. What makes this process different from sonification is a matter of intention and interpretation: How well does the sound represent the data used for sonification? An overview of this problem is addressed by Hermann [27].

  2. 2.

    Two markers were placed near the putter hand grip and the top of the club head. The data acquisition sampling rate was 200 Hz.

  3. 3.

    For this pretest and all experiments described throughout the chapter, subjects wore Sennheiser headphones.

  4. 4.

    A Bark scale is a psychoacoustic scale developed by Edward Zwicker in 1961 [64]. It can be defined as a scale in which equal distances between frequencies correspond with equal distances in perception. The scale ranges from 1 to 24, which corresponds with the first 24 critical bands of hearing.

  5. 5.

    Club head position was used to map sound to stereo.

  6. 6.

    During pretesting, a 25–27 ms latency was measured.

  7. 7.

    To calculate angular velocity in real-time, additional markers would be required and placed near the subject’s shoulder. Moreover, variance in the amount of wrist rotation can greatly affect the club head’s angular velocity. Thus linear velocity across the x-z plane was selected for sonification.

  8. 8.

    A transient is a sound at the beginning of a waveform that has a very short duration and high amplitude. It typically has non-periodic components.

  9. 9.

    A sine wave is continuous and periodic and has as smooth form due to its fundamental relationship to the circle. This differs from the sawtooth wave, which is also continuous, but has the conventional form of ramping up and then dropping sharply.

  10. 10.

    For the second-order IIR filter, the s2m.resFS1\(\sim \) Max/MSP object was used and is available at https://metason.prism.cnrs.fr//Resultats/MaxMSP/.

  11. 11.

    Formants are amplitude peaks in the frequency spectrum of a sound.

  12. 12.

    This scaling choice was purely intuitive. One might imagine a crowd’s “excitement” and frequency as proportional.

  13. 13.

    To better explain how the speed scalar affects brightness, consider when the value of the speed scalar is 0.5, a 1000 Hz fixed-frequency, for example, sine wave oscillator is halved (500 Hz). Thus, velocity, as mapped to the speed scalar, affects the frequencies of the five sine wave oscillators. The following are the frequencies (in Hz) of the five oscillators: 3097, 4495, 5588, 7471, and 11100.

  14. 14.

    A partial is any tone composed in a complex sound.

  15. 15.

    Trials were considered successful if they measured within a distance of 25 cm from the target.

  16. 16.

    A method was developed that takes a subject’s real-time club head speed and position and, using her MVP and mean-acceleration profile (MAP), calculates a real-time error. The error corresponds to the difference between the current estimation time of impact and that of the MVP.

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Acknowledgements

Many thanks to PRISM researchers Richard Kronland-Martinent, Mitsuko Aramaki, and Sølvi Ystad for their guidance and help developing materials that were used in the first two experiments. In addition to Mario LaFortune for his expertise and enthusiasm. This work was funded by the French National Research Agency (ANR) under the SoniMove: Inform, Guide and Learn Actions by Sounds project (ANR-14-CE24-0018-01).

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Authors and Affiliations

  1. Aix Marseille Univ, CNRS, ISM, Marseille, France

    Benjamin O’Brien, Brett Juhas, Marta Bieńkiewicz, Frank Buloup, Lionel Bringnoux & Christophe Bourdin

  2. Aix Marseille Univ, CNRS, PRISM (Perception, Representations, Image, Sound and Music), 31 Chemin J. Aiguier, CS 70071, 13402, Marseille cedex 09, France

    Laurent Pruvost

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  1. Benjamin O’Brien
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Correspondence to Benjamin O’Brien .

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Editors and Affiliations

  1. Laboratoire PRISM, AMU-CNRS, Marseille, France

    Mitsuko Aramaki

  2. INESC TEC, Porto, Portugal

    Matthew E. P. Davies

  3. Laboratoire PRISM, AMU-CNRS, Marseille, France

    Richard Kronland-Martinet

  4. Laboratoire PRISM, AMU-CNRS, Marseille, France

    Sølvi Ystad

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O’Brien, B. et al. (2018). Considerations for Developing Sound in Golf Putting Experiments. In: Aramaki, M., Davies , M., Kronland-Martinet, R., Ystad, S. (eds) Music Technology with Swing. CMMR 2017. Lecture Notes in Computer Science(), vol 11265. Springer, Cham. https://doi.org/10.1007/978-3-030-01692-0_23

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