demonstration

MusicMixer: computer-aided DJ system based on an automatic song mixing

Authors:

Tatsunori Hirai,

Shigeo MorishimaAuthors Info & Claims

ACE '15: Proceedings of the 12th International Conference on Advances in Computer Entertainment Technology

Article No.: 41, Pages 1 - 5

https://doi.org/10.1145/2832932.2832942

Published: 16 November 2015 Publication History

Abstract

In this paper, we present MusicMixer, a computer-aided DJ system that helps DJs, specifically with song mixing. MusicMixer continuously mixes and plays songs using an automatic music mixing method that employs audio similarity calculations. By calculating similarities between song sections that can be naturally mixed, MusicMixer enables seamless song transitions. Though song mixing is the most fundamental and important factor in DJ performance, it is difficult for untrained people to seamlessly connect songs. MusicMixer realizes automatic song mixing using an audio signal processing approach; therefore, users can perform DJ mixing simply by selecting a song from a list of songs suggested by the system, enabling effective DJ song mixing and lowering entry barriers for the inexperienced. We also propose personalization for song suggestions using a preference memorization function of MusicMixer.

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Digital Library

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Cited By

Vande Veire LDe Bie T(2018)From raw audio to a seamless mixEURASIP Journal on Audio, Speech, and Music Processing10.1186/s13636-018-0134-82018:1(1-21)Online publication date: 1-Dec-2018
https://dl.acm.org/doi/10.1186/s13636-018-0134-8
Shi YZhang HRajapakse HPerera NVega Gálvez TNanayakkara SMandryk RHancock MPerry MCox A(2018)GestAKeyProceedings of the 2018 CHI Conference on Human Factors in Computing Systems10.1145/3173574.3174170(1-12)Online publication date: 21-Apr-2018
https://dl.acm.org/doi/10.1145/3173574.3174170

Index Terms

MusicMixer: computer-aided DJ system based on an automatic song mixing
1. Applied computing
  1. Arts and humanities
    1. Sound and music computing
2. Information systems
  1. Information retrieval
    1. Specialized information retrieval
      1. Multimedia and multimodal retrieval
        Music retrieval

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Information & Contributors

Information

Published In

cover image ACM Other conferences

ACE '15: Proceedings of the 12th International Conference on Advances in Computer Entertainment Technology

November 2015

388 pages

ISBN:9781450338523

DOI:10.1145/2832932

General Chairs:
Adrian David Cheok
Imagineering Institute, Malaysia, United Kingdom
,
Mohd Shah Sunar
Universiti Teknologi Malaysia
,
Ken Neo
Multimedia University, Malaysia
,
Program Chair:
Yoram Chisik
University of Madeira, Portugal

Copyright © 2015 Owner/Author.

Permission to make digital or hard copies of part or all 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 third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 16 November 2015

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ACE 2015

ACE 2015: 12th International Conference on Advances in Computer Entertainment Technology

November 16 - 19, 2015

Iskandar, Malaysia

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Overall Acceptance Rate 36 of 90 submissions, 40%

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Citations

Cited By

Vande Veire LDe Bie T(2018)From raw audio to a seamless mixEURASIP Journal on Audio, Speech, and Music Processing10.1186/s13636-018-0134-82018:1(1-21)Online publication date: 1-Dec-2018
https://dl.acm.org/doi/10.1186/s13636-018-0134-8
Shi YZhang HRajapakse HPerera NVega Gálvez TNanayakkara SMandryk RHancock MPerry MCox A(2018)GestAKeyProceedings of the 2018 CHI Conference on Human Factors in Computing Systems10.1145/3173574.3174170(1-12)Online publication date: 21-Apr-2018
https://dl.acm.org/doi/10.1145/3173574.3174170

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