Search Results for author:
Found 6 papers, 1 papers with code
NESC: Robust Neural End-2-End Speech Coding with GANs
Neural networks have proven to be a formidable tool to tackle the problem of speech coding at very low bit rates.
PostGAN: A GAN-Based Post-Processor to Enhance the Quality of Coded Speech
In order to mitigate these coding artefacts and enhance the quality of coded speech, a post-processor that relies on a-priori information transmitted from the encoder is traditionally employed at the decoder side.
A DNN Based Post-Filter to Enhance the Quality of Coded Speech in MDCT Domain
Frequency domain processing, and in particular the use of Modified Discrete Cosine Transform (MDCT), is the most widespread approach to audio coding.
A Streamwise GAN Vocoder for Wideband Speech Coding at Very Low Bit Rate
Recently, GAN vocoders have seen rapid progress in speech synthesis, starting to outperform autoregressive models in perceptual quality with much higher generation speed.
StyleMelGAN: An Efficient High-Fidelity Adversarial Vocoder with Temporal Adaptive Normalization
In recent years, neural vocoders have surpassed classical speech generation approaches in naturalness and perceptual quality of the synthesized speech.
Enhancement Of Coded Speech Using a Mask-Based Post-Filter
The quality of speech codecs deteriorates at low bitrates due to high quantization noise.
