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Listar por tema "intelligibility"

Mostrando ítems 1-4 de 4

    • Deep Neural Networks for Speech Enhancement in Complex-Noisy Environments 

      Saleem, Nasir; Khattak, Muhammad Irfan (International Journal of Interactive Multimedia and Artificial Intelligence (IJIMAI), 03/2020)
      In this paper, we considered the problem of the speech enhancement similar to the real-world environments where several complex noise sources simultaneously degrade the quality and intelligibility of a target speech. The ...

    • Efficient Gated Convolutional Recurrent Neural Networks for Real-Time Speech Enhancement 

      Fazal-E -Wahab; Ye, Zhongfu; Saleem, Nasir; Ali, Hamza (International Journal of Interactive Multimedia and Artificial Intelligence, 2024)
      Deep learning (DL) networks have grown into powerful alternatives for speech enhancement and have achieved excellent results by improving speech quality, intelligibility, and background noise suppression. Due to high ...

    • Regularized sparse features for noisy speech enhancement using deep neural networks 

      Khattak, Muhammad Irfan; Saleem, Nasir; Gao, Jiechao; Verdú, Elena ; Parra Fuente, Javier (Computers and Electrical Engineering, 2022)
      A speech enhancement algorithm improves the perceptual aspects of a speech degraded by noise signals. We propose a phase-aware deep neural network (DNN) using the regularized sparse features for speech enhancement. A ...

    • Spectral phase estimation based on deep neural networks for single channel speech enhancement 

      Saleem, N.; Khattak, Muhammad Irfan; Verdú, Elena (Journal of Communications Technology and Electronics, 12/2019)
      Majority of speech processing algorithms operate only with the spectral magnitude, leaving spectral phase unstructured and unexplored. With recent advancement in deep neural networks (DNNs), the phase processing became ...