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Automatic recognition of vocal reactions in music listening using smart earbuds: poster abstract

Published: 16 November 2020 Publication History

Abstract

We propose an in-ear sensing method that automatically detects vocal reactions that people often exhibit when listening to music. We observe what kind of vocal reactions are often brought during music listening and investigate the challenges of applying an existing representative acoustic classification model to vocal reaction recognition. We present our vocal reaction recognition method and the preliminary evaluation to assess its performance.

References

[1]
[n.d.]. Music Listening 2019. https://www.ifpi.org/wp-content/uploads/2020/07/Music-Listening-2019-1.pdf. Accessed: September 30, 2020.
[2]
[n.d.]. YAMNet. https://github.com/tensorflow/models/tree/master/research/audioset/yamnet. Accessed: September 23, 2020.
[3]
Andrew G Howard, Menglong Zhu, Bo Chen, Dmitry Kalenichenko, Weijun Wang, Tobias Weyand, Marco Andreetto, and Hartwig Adam. 2017. Mobilenets: Efficient convolutional neural networks for mobile vision applications. arXiv preprint arXiv:1704.04861 (2017).

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  • (2024)Artificial intelligence for predicting orthodontic patient cooperation: Voice records versus frontal photographsAPOS Trends in Orthodontics10.25259/APOS_221_2023(1-9)Online publication date: 18-Jan-2024
  • (2024)Speech-based personality prediction using deep learning with acoustic and linguistic embeddingsScientific Reports10.1038/s41598-024-81047-014:1Online publication date: 3-Dec-2024

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  1. Automatic recognition of vocal reactions in music listening using smart earbuds: poster abstract

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    cover image ACM Conferences
    SenSys '20: Proceedings of the 18th Conference on Embedded Networked Sensor Systems
    November 2020
    852 pages
    ISBN:9781450375900
    DOI:10.1145/3384419
    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: 16 November 2020

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    Author Tags

    1. musing listening
    2. reaction classification
    3. vocal reaction

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    • Ministry of Science, ICT

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    Overall Acceptance Rate 198 of 990 submissions, 20%

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    Cited By

    View all
    • (2024)Artificial intelligence for predicting orthodontic patient cooperation: Voice records versus frontal photographsAPOS Trends in Orthodontics10.25259/APOS_221_2023(1-9)Online publication date: 18-Jan-2024
    • (2024)Speech-based personality prediction using deep learning with acoustic and linguistic embeddingsScientific Reports10.1038/s41598-024-81047-014:1Online publication date: 3-Dec-2024

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