3 accepted papers
Whisper to Normal voice conversion (W2N) holds great promise for assistive communication and healthcare, making it an exciting area of research and development. Recent advancements in W2N are predominantly driven by self-supervised speech representation learning (SSL) techniques. While effective, SS…
One of the important tasks of auditory attention decoding is to identify the attended speaker’s direction from the listener’s EEG signals. Compared to rule-based methods, deep neural networks (DNNs) have recently shown significantly better identification accuracy, especially with short decision wind…
Perceptual evaluation of speech quality (PESQ) is widely accepted as an effective objective metric closely related to the speech quality sensed by human listening perception. Due to its evaluation complexity and non-differentiability, PESQ is difficult to include in the cost function for deep learni…