Project Details

Sequence summarizing neural networks for speaker recognition

Project Period: 1. 7. 2016 – 30. 6. 2019

Project Type: grant

Code: 5SA15094

Agency: Evropská unie

Program: Horizon 2020

Czech title
Neuronové sítě shrnující sekvence pro rozpoznávání mluvčího
Type
grant
Keywords

Speaker recognition, Neural networks

Abstract

The proposed project deals with speaker recognition and is motivated by the huge
performance gains that, in recent years, have been brought to other recognition
tasks by so called neural networks (NN)s. The objective of the proposal is to
develop a new type of NN that is suitable for speaker recognition and take it to
the state where it is ready for practical use. So far, attempts to take advantage
of NNs in speaker recognition have replaced one or more components in the
state-of-the-art speaker recognition chain with NN equivalencies. However, this
approach has the same limitations as the state-of-art processing chain in terms
of what kind of patterns in the speech signals that be can modeled. Instead, our
proposed project aims at replacing the whole speaker recognition chain with one
NN that process whole utterances in one step. This approach should take better
advantage of NNs ability to model complex patterns in the speech signals. The
objectives of the proposal will be achieved by theoretical work (derivation of NN
structure, training criteria etc.), implementation (parallelization, scalability
etc.) and careful testing on real speech data (finding appropriate default
settings etc.).

Team members
Publications

2020

2019

2018

2017

2016

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