Use this URL to cite or link to this record in EThOS:
Title: Advanced automatic mixing tools for music
Author: Perez Gonzalez, Enrique
ISNI:       0000 0004 2725 131X
Awarding Body: Queen Mary, University of London
Current Institution: Queen Mary, University of London
Date of Award: 2010
Availability of Full Text:
Access from EThOS:
Access from Institution:
This thesis presents research on several independent systems that when combined together can generate an automatic sound mix out of an unknown set of multi‐channel inputs. The research explores the possibility of reproducing the mixing decisions of a skilled audio engineer with minimal or no human interaction. The research is restricted to non‐time varying mixes for large room acoustics. This research has applications in dynamic sound music concerts, remote mixing, recording and postproduction as well as live mixing for interactive scenes. Currently, automated mixers are capable of saving a set of static mix scenes that can be loaded for later use, but they lack the ability to adapt to a different room or to a different set of inputs. In other words, they lack the ability to automatically make mixing decisions. The automatic mixer research depicted here distinguishes between the engineering mixing and the subjective mixing contributions. This research aims to automate the technical tasks related to audio mixing while freeing the audio engineer to perform the fine‐tuning involved in generating an aesthetically‐pleasing sound mix. Although the system mainly deals with the technical constraints involved in generating an audio mix, the developed system takes advantage of common practices performed by sound engineers whenever possible. The system also makes use of inter‐dependent channel information for controlling signal processing tasks while aiming to maintain system stability at all times. A working implementation of the system is described and subjective evaluation between a human mix and the automatic mix is used to measure the success of the automatic mixing tools.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available
Keywords: Electronic Engineering