hpDJ: An Automated DJ with Floorshow Feedback
暂无分享,去创建一个
The hpDJ system described here goes some way towards replacing the tasks performed by human DJs. It has potential use as a component in the user-interface to audio-based consumer digital entertainment systems, converting the audio data stored on such systems from a set of songs into a continuous seamless mix. Such mixes are suitable for play-out over streaming media (e.g., in personalized internet radio), or for writing to an appropriate recording medium (such as CD, the hard disk of an iPod, or a flash ROM card) for subsequent playback, or for playing to crowds of dancers in real nightclubs. Results from the nightclub experiment are promising, and our subsequent development of monitoring technology allows crowd feedback to influence hpDJ’s choices of songs, making it even more human-like. The use of human-inspired heuristics in dynamically selecting customized DSP filters for the cross-fade has the potential to allow hpDJ to perform cross-fades in ways that would be virtually impossible for a human DJ playing live. While there is a growing market for software products that give a “virtual” version of traditional human-DJ hardware, and while MixMeister provides a pleasant interface to a set of software tools that allow an unskilled human to create professional-quality continuous mixes, hpDJ as described here is as far as we know the first and only system that aims to totally automate the tasks performed by a human nightclub DJ, including dynamically reacting to the responses from the crowd in real-time. Although we have yet to test Version 2 in a real nightclub, it is clear that the prospect of crowd monitoring opens up new possibilities for the computer-assisted composition of music. But, whereas most computer-aided music composition systems assume a single human author working with the machine, the vision in hpDJ is that the author is an entire crowd of participants, collaborating indirectly, giving feedback as they consume the music. That feedback being generated either actively by the members of the crowd hitting the buttons on their voting watches; or passively by them merely dancing and having a good time, while the computer watches them.
[1] Melanie Mitchell,et al. An introduction to genetic algorithms , 1996 .
[2] Eric D. Scheirer,et al. Tempo and beat analysis of acoustic musical signals. , 1998, The Journal of the Acoustical Society of America.
[3] D. E. Goldberg,et al. Genetic Algorithms in Search , 1989 .
[4] Bill Brewster,et al. How to DJ Right: The Art and Science of Playing Records , 2003 .
[5] David E. Goldberg,et al. Genetic Algorithms in Search Optimization and Machine Learning , 1988 .