Adaptive Filtering for Multi-Track Audio Based on Time–Frequency Masking Detection

There is a growing need to facilitate the production of recorded music as independent musicians are now key in preserving the broader cultural roles of music. A critical component of the production of music is multitrack mixing, a time-consuming task aimed at, among other things, reducing spectral m...

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Main Authors: Wenhan Zhao, Fernando Pérez-Cota
Format: Article
Language:English
Published: MDPI AG 2024-10-01
Series:Signals
Subjects:
Online Access:https://www.mdpi.com/2624-6120/5/4/35
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author Wenhan Zhao
Fernando Pérez-Cota
author_facet Wenhan Zhao
Fernando Pérez-Cota
author_sort Wenhan Zhao
collection DOAJ
description There is a growing need to facilitate the production of recorded music as independent musicians are now key in preserving the broader cultural roles of music. A critical component of the production of music is multitrack mixing, a time-consuming task aimed at, among other things, reducing spectral masking and enhancing clarity. Traditionally, this is achieved by skilled mixing engineers relying on their judgment. In this work, we present an adaptive filtering method based on a novel masking detection scheme capable of identifying masking contributions, including temporal interchangeability between the masker and maskee. This information is then systematically used to design and apply filters. We implement our methods on multitrack music to improve the quality of the raw mix.
format Article
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institution Kabale University
issn 2624-6120
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spelling doaj-art-b32b40a3388c4541a80e12404e8d4b242024-12-27T14:53:35ZengMDPI AGSignals2624-61202024-10-015463364110.3390/signals5040035Adaptive Filtering for Multi-Track Audio Based on Time–Frequency Masking DetectionWenhan Zhao0Fernando Pérez-Cota1Department of Electric and Electronic Engineering, Faculty of Engineering, University of Nottingham, Nottingham NG7 2RD, UKDepartment of Electric and Electronic Engineering, Faculty of Engineering, University of Nottingham, Nottingham NG7 2RD, UKThere is a growing need to facilitate the production of recorded music as independent musicians are now key in preserving the broader cultural roles of music. A critical component of the production of music is multitrack mixing, a time-consuming task aimed at, among other things, reducing spectral masking and enhancing clarity. Traditionally, this is achieved by skilled mixing engineers relying on their judgment. In this work, we present an adaptive filtering method based on a novel masking detection scheme capable of identifying masking contributions, including temporal interchangeability between the masker and maskee. This information is then systematically used to design and apply filters. We implement our methods on multitrack music to improve the quality of the raw mix.https://www.mdpi.com/2624-6120/5/4/35adaptive filteringmultitrack mixingauditory masking
spellingShingle Wenhan Zhao
Fernando Pérez-Cota
Adaptive Filtering for Multi-Track Audio Based on Time–Frequency Masking Detection
Signals
adaptive filtering
multitrack mixing
auditory masking
title Adaptive Filtering for Multi-Track Audio Based on Time–Frequency Masking Detection
title_full Adaptive Filtering for Multi-Track Audio Based on Time–Frequency Masking Detection
title_fullStr Adaptive Filtering for Multi-Track Audio Based on Time–Frequency Masking Detection
title_full_unstemmed Adaptive Filtering for Multi-Track Audio Based on Time–Frequency Masking Detection
title_short Adaptive Filtering for Multi-Track Audio Based on Time–Frequency Masking Detection
title_sort adaptive filtering for multi track audio based on time frequency masking detection
topic adaptive filtering
multitrack mixing
auditory masking
url https://www.mdpi.com/2624-6120/5/4/35
work_keys_str_mv AT wenhanzhao adaptivefilteringformultitrackaudiobasedontimefrequencymaskingdetection
AT fernandoperezcota adaptivefilteringformultitrackaudiobasedontimefrequencymaskingdetection