Výsledky vyhledávání - "Heymans, Walter"

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Efficient acoustic feature transformation in mismatched environments using a Guided-GAN

Autor: Heymans, Walter, Davel, Marelie H., van Heerden, Charl

Publikováno v: Speech Communication, 143, pp.10-20 (2022)

We propose a new framework to improve automatic speech recognition (ASR) systems in resource-scarce environments using a generative adversarial network (GAN) operating on acoustic input features. The GAN is used to enhance the features of mismatched

Externí odkaz: http://arxiv.org/abs/2210.00721

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Multi-style Training for South African Call Centre Audio

Autor: Heymans, Walter, Davel, Marelie H., van Heerden, Charl

Publikováno v: Artificial Intelligence Research 2022

Mismatched data is a challenging problem for automatic speech recognition (ASR) systems. One of the most common techniques used to address mismatched data is multi-style training (MTR), a form of data augmentation that attempts to transform the train

Externí odkaz: http://arxiv.org/abs/2202.07219

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Automatic speech recognition of poor quality audio using generative adversarial networks

Autor: Heymans, Walter

MEng (Computer and Electronic Engineering), North-West University, Potchefstroom Campus In this study, we investigate the use of generative adversarial networks (GANs) to improve speech recognition performance of poor quality audio obtained from a re

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=od______1399::507b8d2f15eadd6d0e2296a5991d52cb
https://hdl.handle.net/10394/39346

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