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GeoTracks: Adaptive Music for Everyday Journeys

Published: 01 October 2016 Publication History

Abstract

Listening to music on the move is an everyday activity for many people. This paper proposes geotracks and geolists, music tracks and playlists of existing music that are aligned and adapted to specific journeys. We describe how everyday walking journeys such as commutes to work and existing popular music tracks can each be analysed, decomposed and then brought together, using musical adaptations including skipping and repeating parts of tracks, dynamically remixing tracks and cross-fades. Using a naturalistic experiment we compared walking while listening to geotracks (dynamically adapted using GPS location information) to walking while listening to a fixed playlist. Overall, participants enjoyed the walk more when listening to the adaptive geotracks. However adapting the lengths of tracks appeared to detract from the experience of the music in some situations and for some participants, revealing trade-offs in achieving fine-grained alignment of music and walking journeys.

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Cited By

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  • (2023)AI-to-Human ActuationProceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies10.1145/35808127:1(1-32)Online publication date: 28-Mar-2023
  • (2020)Context-Aware Music Recommender System Based on Automatic Detection of the User’s Physical ActivityDistributed Computing and Artificial Intelligence, 17th International Conference10.1007/978-3-030-53036-5_15(142-151)Online publication date: 7-Aug-2020
  • (2019)Adaptive Musical SoundtracksProceedings of the 14th International Audio Mostly Conference: A Journey in Sound10.1145/3356590.3356597(31-38)Online publication date: 18-Sep-2019
  • Show More Cited By

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cover image ACM Conferences
MM '16: Proceedings of the 24th ACM international conference on Multimedia
October 2016
1542 pages
ISBN:9781450336031
DOI:10.1145/2964284
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: 01 October 2016

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Author Tags

  1. adaptive
  2. commute
  3. experience
  4. geolist
  5. geotrack
  6. mobile
  7. music
  8. pedestrian
  9. soundtrack
  10. walk

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  • Short-paper

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MM '16
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MM '16: ACM Multimedia Conference
October 15 - 19, 2016
Amsterdam, The Netherlands

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MM '16 Paper Acceptance Rate 52 of 237 submissions, 22%;
Overall Acceptance Rate 2,145 of 8,556 submissions, 25%

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Cited By

View all
  • (2023)AI-to-Human ActuationProceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies10.1145/35808127:1(1-32)Online publication date: 28-Mar-2023
  • (2020)Context-Aware Music Recommender System Based on Automatic Detection of the User’s Physical ActivityDistributed Computing and Artificial Intelligence, 17th International Conference10.1007/978-3-030-53036-5_15(142-151)Online publication date: 7-Aug-2020
  • (2019)Adaptive Musical SoundtracksProceedings of the 14th International Audio Mostly Conference: A Journey in Sound10.1145/3356590.3356597(31-38)Online publication date: 18-Sep-2019
  • (2019)Semantic Web Technology for New Experiences Throughout the Music Production-Consumption Chain2019 International Workshop on Multilayer Music Representation and Processing (MMRP)10.1109/MMRP.2019.00017(49-55)Online publication date: Jan-2019
  • (2017)The Rough MileProceedings of the 12th International Audio Mostly Conference on Augmented and Participatory Sound and Music Experiences10.1145/3123514.3123540(1-8)Online publication date: 23-Aug-2017
  • (2017)The Rough MileProceedings of the 2017 Conference on Designing Interactive Systems10.1145/3064663.3064756(877-888)Online publication date: 10-Jun-2017

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