Erratum: Musical training, individual differences and the cocktail party problem
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In the Supplementary Information file originally published with this Article, there is a typographical error in Affiliation 2 " This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article's Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit
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Musical training, individual differences and the cocktail party problem
Are musicians better able to understand speech in noise than non-musicians? Recent findings have produced contradictory results. Here we addressed this question by asking musicians and non-musicians to understand target sentences masked by other sentences presented from different spatial locations, the classical 'cocktail party problem' in speech science. We found that musicians obtained a subs...
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We propose an algorithm to separate simultaneously speaking persons from each other, the “cocktail party problem”, using a single microphone. Our approach involves a deep recurrent neural networks regression to a vector space that is descriptive of independent speakers. Such a vector space can embed empirically determined speaker characteristics and is optimized by distinguishing between speake...
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