Despite recent progress in generative adversarial network (GAN)-based vocoders, where
the model generates raw waveform conditioned on acoustic features, it is challenging to …

We present a causal speech enhancement model working on the raw waveform that runs in
real-time on a laptop CPU. The proposed model is based on an encoder-decoder …

The INTERSPEECH 2020 Deep Noise Suppression (DNS) Challenge is intended to
promote collaborative research in real-time single-channel Speech Enhancement aimed to …

Human subjective evaluation is the" gold standard" to evaluate speech quality optimized for
human perception. Perceptual objective metrics serve as a proxy for subjective scores. The …

Human subjective evaluation is the" gold standard" to evaluate speech quality optimized for
human perception. Perceptual objective metrics serve as a proxy for subjective scores. We …

The Deep Noise Suppression (DNS) challenge is designed to foster innovation in the area
of noise suppression to achieve superior perceptual speech quality. We recently organized …

The Deep Noise Suppression (DNS) challenge is designed to foster innovation in the area
of noise suppression to achieve superior perceptual speech quality. We recently organized …

This paper investigates several aspects of training a RNN (recurrent neural network) that
impact the objective and subjective quality of enhanced speech for real-time single-channel …

The recent surge in the use of Deep Neural Networks (DNNs) has also made its mark in the
field of Audio Enhancement (AE), providing much better quality than the classical methods …

Much recent work on Spoken Language Understanding (SLU) is limited in at least one of
three ways: models were trained on oracle text input and neglected ASR errors, models …