New Sonorities for Early Jazz Recordings Using Sound Source Separation and Automatic Mixing Tools

نویسندگان

  • Daniel Matz
  • Estefanía Cano
  • Jakob Abeßer
چکیده

In this paper, a framework for automatic mixing of early jazz recordings is presented. In particular, we propose the use of sound source separation techniques as a preprocessing step of the mixing process. In addition to an initial solo and accompaniment separation step, the proposed mixing framework is composed of six processing blocks: harmonic-percussive separation (HPS), cross-adaptive multi-track scaling (CAMTS), cross-adaptive equalizer (CAEQ), cross-adaptive dynamic spectral panning (CADSP), automatic excitation (AE), and time-frequency selective panning (TFSP). The effects of the different processing steps in the final quality of the mix are evaluated through a listening test procedure. The results show that the desired quality improvements in terms of sound balance, transparency, stereo impression, timbre, and overall impression can be achieved with the proposed framework.

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تاریخ انتشار 2015