Listar por tema 

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, 05/2023)
      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 ...