Faculty of Information Technology, BUT

Project Details

Sequence summarizing neural networks for speaker recognition

Project Period: 01.07.2016 - 30.06.2019

Code: 5SA15094

Agency: South Moravian Region

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
Rohdin Johan A., Dr. (UPGM FIT VUT) , research leader
Burget Lukáš, doc. Ing., Ph.D. (UPGM FIT VUT) , team leader
Otáhalová Sylva (UPGM FIT VUT)
Publications

2019

2018

2017

2016

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