Audio-visual speech enhancement is the task of improving the quality of a speech signal
when video of the speaker is available. It opens-up the opportunity of improving speech …

Recent end-to-end text-to-speech synthesis (TTS) systems have successfully synthesized
high-quality speech. However, TTS speech intelligibility degrades in noisy environments …

In speech enhancement, MetricGAN-based approaches reduce the discrepancy between
the $ L_p $ loss and evaluation metrics by utilizing a non-differentiable evaluation metric as …

The paper aims to discuss a case study of sensing analytics and technology in acoustics
when applied to reverberation conditions. Reverberation is one of the issues that makes …

The intelligibility of speech severely degrades in the presence of environmental noise and
reverberation. In this paper, we propose a novel deep learning based system for modifying …

This paper presents SaSLaW, a spontaneous dialogue speech corpus containing
synchronous recordings of what speakers speak, listen to, and watch. Humans consider the …

We present the beta version of ASE (the Automatic Sound Engineer), a NELE (Near End
Listening Enhancement) algorithm based on audio engineering knowledge. Generations of …

This study focuses on identifying effective features for controlling speech to increase speech
intelligibility under adverse conditions. Previous approaches either cancel noise throughout …

We present a neural text-to-speech (TTS) method that models natural vocal effort variation to
improve the intelligibility of synthetic speech in the presence of noise. The method consists …

Listeners are routinely exposed to many different types of speech, including artificially-
enhanced and synthetic speech, styles which deviate to a greater or lesser extent from …