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Case Studies to Enhance Collectively Sharing Human Hearing: Ambient Sounds Memory and Mindful Speaker

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Book cover Distributed, Ambient and Pervasive Interactions. Smart Living, Learning, Well-being and Health, Art and Creativity (HCII 2022)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 13326))

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Abstract

Our everyday life is filled with a variety of serendipitous and beautiful sounds that are both natural and artificial. We consciously also unconsciously enjoy these sounds. The sounds are one of the most important factor in our daily life, thus it is a promising direction to use such sounds to develop innovative digital services. In this paper, after presenting a brief overview of our digital platform named CollectiveEars, we show two case studies to use CollectiveEars as an underlying platform to exploit to use the captured diverse sounds in the world. The first case study is named Ambient Sounds Memory and the second case study is named Mindful Speaker. These case studies show the feasibilities to use CollectiveEars to develop future innovative digital services.

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Authors and Affiliations

  1. Department of Computer Science and Engineering, Waseda University, Tokyo, Japan

    Risa Kimura & Tatsuo Nakajima

Authors
  1. Risa Kimura
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  2. Tatsuo Nakajima
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Correspondence to Risa Kimura .

Editor information

Editors and Affiliations

  1. Smart Future Initiative, Frankfurt am Main, Germany

    Norbert A. Streitz

  2. Kyushu University, Fukuoka, Japan

    Shin'ichi Konomi

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Kimura, R., Nakajima, T. (2022). Case Studies to Enhance Collectively Sharing Human Hearing: Ambient Sounds Memory and Mindful Speaker. In: Streitz, N.A., Konomi, S. (eds) Distributed, Ambient and Pervasive Interactions. Smart Living, Learning, Well-being and Health, Art and Creativity. HCII 2022. Lecture Notes in Computer Science, vol 13326. Springer, Cham. https://doi.org/10.1007/978-3-031-05431-0_26

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  • DOI: https://doi.org/10.1007/978-3-031-05431-0_26

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-05430-3

  • Online ISBN: 978-3-031-05431-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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