Towards Automatic Reverb Addition for Production Oriented Multi-Track Audio Mixing

Master Thesis (2017)
Author(s)

A. Pujahari (TU Delft - Electrical Engineering, Mathematics and Computer Science)

Contributor(s)

Cynthia C.S. Liem – Mentor

A Hanjalic – Graduation committee member

D.J. Broekens – Graduation committee member

Faculty
Electrical Engineering, Mathematics and Computer Science
Copyright
© 2017 Abhinav Pujahari
More Info
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Publication Year
2017
Language
English
Copyright
© 2017 Abhinav Pujahari
Graduation Date
23-08-2017
Awarding Institution
Delft University of Technology
Programme
['Electrical Engineering']
Related content

Link to Audio Files and Code

https://github.com/a-pujahari
Faculty
Electrical Engineering, Mathematics and Computer Science
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Abstract

Sound spatialization is a natural, intuitive but sparsely researched topic in multi-track audio mixing. Although a lot of research has been devoted to the automatic fader gain settings, addition of dynamic range equalization and related effects, delay and Reverb have taken a backseat. The dichotomy in the artistic and engineering approaches to audio mixing have resulted in studio best practices not given their due with suitable algorithmic interpretations.
Due regard to studio practices along with a more holistic approach combining all the steps of audio mixing are especially necessary in the background of the exponential growth of bedroom studio producers and musicians, mixing and crafting their tracks personally. The additional growth in the availability of faster personal computing only fuels this trend.
This thesis attempts to be an exploratory foray into the addition of Reverb to production oriented multi-track mixing. Taking into account studio practices, 2 different algorithms are compared with a professionally mixed track and an unreverberated reference track. The results from hidden reference listening tests are analyzed to draw conclusions of the effectiveness of automatic methods of Reverb addition against the professionally mixed track.
The results suggest that the current algorithms implemented are unable to reach the subjective perceptual quality of the professionally mixed track. However, some important conclusions are drawn from the theoretical and experimental research which provide clear guidelines for possible future implementations.

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