Speaker Verification on Unbalanced Data with Genetic Programming
Created by W.Langdon from
gp-bibliography.bib Revision:1.8129
- @InProceedings{EvoIasp16Loughranetal,
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author = "Roisin Loughran and Alexandros Agapitos and
Ahmed Kattan and Anthony Brabazon and Michael O'Neill",
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title = "Speaker Verification on Unbalanced Data with Genetic
Programming",
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booktitle = "19th European Conference on the Applications of
Evolutionary Computation",
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year = "2016",
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editor = "Giovanni Squillero and Paolo Burelli",
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series = "Lecture Notes in Computer Science",
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volume = "9597",
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pages = "737--753",
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address = "Porto, Portugal",
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month = mar # " 30 - " # apr # " 1",
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organisation = "EvoStar",
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publisher = "Springer",
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keywords = "genetic algorithms, genetic programming, Speaker
verification, Unbalanced data, Feature selection",
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URL = "http://dx.doi.org/10.1007/978-3-319-31204-0_47",
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DOI = "doi:10.1007/978-3-319-31204-0_47",
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abstract = "Automatic Speaker Verification (ASV) is a highly
unbalanced binary classification problem, in which any
given speaker must be verified against everyone else.
We apply Genetic programming (GP) to this problem with
the aim of both prediction and inference. We examine
the generalisation of evolved programs using a variety
of fitness functions and data sampling techniques found
in the literature. A significant difference between
train and test performance, which can indicate
overfitting, is found in the evolutionary runs of all
to-be-verified speakers. Nevertheless, in all speakers,
the best test performance attained is always superior
than just merely predicting the majority class. We
examine which features are used in good-generalising
individuals. The findings can inform future
applications of GP or other machine learning techniques
to ASV about the suitability of feature-extraction
techniques.",
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notes = "EvoApplications2016 held in conjunction with
EuroGP'2016, EvoCOP2016 and EvoMusArt2016",
- }
Genetic Programming entries for
Roisin Loughran
Alexandros Agapitos
Ahmed Kattan
Anthony Brabazon
Michael O'Neill
Citations