1 citations · 1 across the 4 of their papers we have counts for
4 papers
Real-Time Packet Loss Concealment With Mixed Generative and Predictive Model
Jean-Marc Valin, Ahmed Mustafa, Christopher Montgomery +4
As deep speech enhancement algorithms have recently demonstrated capabilities greatly surpassing their traditional counterparts for suppressing noise, reverberation and echo, atten…
A Streamwise GAN Vocoder for Wideband Speech Coding at Very Low Bit Rate
Ahmed Mustafa, Jan Büthe, Srikanth Korse +3
Recently, GAN vocoders have seen rapid progress in speech synthesis, starting to outperform autoregressive models in perceptual quality with much higher generation speed. However,…
StyleMelGAN: An Efficient High-Fidelity Adversarial Vocoder with Temporal Adaptive Normalization
Ahmed Mustafa, Nicola Pia, Guillaume Fuchs
In recent years, neural vocoders have surpassed classical speech generation approaches in naturalness and perceptual quality of the synthesized speech. Computationally heavy models…
Analysis by Adversarial Synthesis -- A Novel Approach for Speech Vocoding
Ahmed Mustafa, Arijit Biswas, Christian Bergler +2
Classical parametric speech coding techniques provide a compact representation for speech signals. This affords a very low transmission rate but with a reduced perceptual quality o…