@inproceedings{c4237c50a5f44374ba8ed1459f2a3bee,
title = "Remedying Sound Source Separation via Azimuth Discrimination and Re-synthesis",
abstract = "Commercially recorded music since the 1950s has been mixed down from many input sound sources to a two-channel reproduction of these sources. The effect of this approach is to assign sources to locations in a stereo field using a pan-position for each source. The Adress algorithm is a popular way of extracting individual music sound sources from a stereo mixture. A drawback of the Adress algorithm is that when time-frequency components in the stereo mixture are shared between two or more sources, calculating the inter-aural intensity scaling parameter for each source for that time-frequency component is challenging. We show how to obtain a good quality inverse of the pan-mixing process in the time-frequency components which are shared between different sources using a new method called Redress. We demonstrate that we can estimate how much of each source is active in time-frequency components which are shared between sources for two and three-source music mixtures. The consequence of this is that audible artefacts are not as prominent in the source estimates.",
keywords = "Music Signal Processing, Source Separation, Time-Frequency",
author = "{De Frein}, Ruairi",
note = "Publisher Copyright: {\textcopyright} 2020 IEEE.; 31st Irish Signals and Systems Conference, ISSC 2020 ; Conference date: 11-06-2020 Through 12-06-2020",
year = "2020",
month = jun,
doi = "10.1109/ISSC49989.2020.9180181",
language = "English",
series = "2020 31st Irish Signals and Systems Conference, ISSC 2020",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "2020 31st Irish Signals and Systems Conference, ISSC 2020",
address = "United States",
}