Search Results for author:
Found 4 papers, 4 papers with code
Coded Speech Quality Measurement by a Non-Intrusive PESQ-DNN
We illustrate the potential of this model by predicting the PESQ scores of wideband-coded speech obtained from AMR-WB or EVS codecs operating at different bitrates in noisy, tandeming, and error-prone transmission conditions.
Principled Pruning of Bayesian Neural Networks through Variational Free Energy Minimization
Bayesian model reduction provides an efficient approach for comparing the performance of all nested sub-models of a model, without re-evaluating any of these sub-models.
A Perceptual Weighting Filter Loss for DNN Training in Speech Enhancement
Single-channel speech enhancement with deep neural networks (DNNs) has shown promising performance and is thus intensively being studied.
Convolutional Neural Networks to Enhance Coded Speech
Enhancing coded speech suffering from far-end acoustic background noise, quantization noise, and potentially transmission errors, is a challenging task.
