Browsing by Advisor/Supervisor

Now showing items 1-16 of 16

    • Activation functions in deep neural networks 

      Pretorius, A.M. (North-West University (South Africa), 2020)
      The ability of machine learning algorithms to generalize is arguably their most important aspect as it determines their ability to perform appropriately on unseen data. The impres-sive generalization abilities of deep ...

    • Automatic Recognition of Code-Switched Speech in Sepedi 

      Modipa, Thipe Isaaih (2016)
      Code switching (CS) is a natural phenomenon that is often observed in multilingual speakers. These speakers use words, phrases or sentences from foreign languages and embed them in sentences in the primary language. ...

    • Automatic speech recognition of poor quality audio using generative adversarial networks 

      Heymans, Walter (North-West University (South Africa)., 2022)
      In this study, we investigate the use of generative adversarial networks (GANs) to improve speech recognition performance of poor quality audio obtained from a real-world source. A GAN is developed to transform acoustic ...

    • Channel estimation and equalisation using generative adversarial networks 

      Oosthuizen, Andrew John (North-West University (South Africa)., 2023)
      Channel State Information (CSI) estimators are used in everyday communication systems to estimate channel impairments that affect transmitted data, and to equalise the impaired data to a more accurate state. However, ...

    • Contrasting Convolutional Neural Networks with alternative architectures for transformation invariance 

      Mouton, Coenraad (North-West University (South Africa), 2021)
      Convolutional Neural Networks (CNNs) have become the standard for image classification tasks, however, they are not completely invariant to transformations of the input image. We empirically investigate to which degree CNNs ...

    • Data sufficiency analysis for automatic speech recognition 

      Badenhorst, Jacob Andreas Cornelius (North-West University, 2009)
      The languages spoken in developing countries are diverse and most are currently under-resourced from an automatic speech recognition (ASR) perspective. In South Africa alone, 10 of the 11 official languages belong to this ...

    • Deep neural networks for prediction of solar flares 

      Krynauw, D.D. (North-West University (South Africa), 2021)
      Solar flares are enormous explosions on the solar surface that originates from sunspots, which could cause damage to satellites, power grids and radio communication systems. Having early-warning systems that could accurately ...

    • Domain adaptation for speaker diarisation in low-resource environments 

      Van Wyk, Lucas (North-West University (South Africa)., 2022)
      Speaker diarisation systems aim to answer the question \who spoke when?" and are useful in providing valuable metadata to downstream applications, such as automatic speech recognition systems. However, speaker diarisation ...

    • Effective automatic speech recognition data collection for under–resourced languages 

      De Vries, Nicolaas Johannes (North-West University, 2011)
      As building transcribed speech corpora for under–resourced languages plays a pivotal role in developing automatic speech recognition (ASR) technologies for such languages, a key step in developing these technologies is the ...

    • Exploring data utilisation in neural networks 

      Haasbroek, Daniël Gerbrand (North-West University (South Africa)., 2022)
      The generalisation ability of deep neural networks differs somewhat from that of more traditional models. Speciőcally, large networks that have the ability to łmemorisež the training data can still generalise well, ...

    • Generalization in deep learning : bilateral synergies in MLP learning 

      Theunissen, Marthinus Wilhelmus (North-West University (South Africa)., 2021)
      We present an investigation of how simple artificial neural networks (specifcally, feed-forward networks with full connections between each successive pair of layers) generalize to out-of-sample data. By emphasizing the ...

    • Interpretability of deep neural networks for SYM-H prediction 

      Beukes, J.P. (North-West University (South Africa), 2021)
      Deep neural networks (DNNs) have shown impressive performance on a wide variety of applications, but it remains di cult to interpret these models. For regression modelling, DNNs generally do not explicitly provide any ...

    • Interpreting deep neural networks with sample sets 

      Venter, Arthur Edgar William (North-West University (South Africa)., 2022)
      Despite their impressive performances on a range of widespread tasks, deep neural networks (DNNs) are generally considered `black box' models due to the lack of transparency behind their decision-making processes. ...

    • Parametric studies of translation invariance and distortion robustness in Convolutional Neural Networks 

      Myburgh, Johannes Christiaan (North-West University (South Africa), 2021)
      Although Convolutional Neural Networks (CNNs) are widely used, their translation in-variance (ability to deal with translated inputs) is still subject to some controversy. We explore this question using translation-sensitivity ...

    • Traffic flow prediction with graph convolutional networks 

      Oosthuizen, Marko Cornelius (North-West University (South Africa)., 2023)
      Traffic flow prediction is a complex task utilising both spatial and temporal information in order to predict the expected speed of traffic at different points in a transportation network. We study the use of graph ...

    • Trajectory modelling with limited speech data 

      Badenhorst, Jacob Andreas Cornelius (2016)
      State-of-the-art automatic speech recognition (ASR) systems are built using hundreds or even thousands of hours of speech data. Even then, high recognition accuracy is achievable only by carefully constraining the recognition ...