The ICASSP 2023 Deep Noise Suppression (DNS) Challenge marks the fifth edition of the
DNS challenge series. DNS challenges were organized from 2019 to 2023 to foster …

Motivated by the success of T5 (Text-To-Text Transfer Transformer) in pre-trained natural
language processing models, we propose a unified-modal SpeechT5 framework that …

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 …

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 …

Sub-band models have achieved promising results due to their ability to model local
patterns in the spectrogram. Some studies further improve the performance by fusing sub …

Convolution-augmented transformer (conformer) has recently shown competitive results in
speech-domain applications, such as automatic speech recognition, continuous speech …

With recent research advancements, deep learning models are be-coming attractive and
powerful choices for speech enhancement in real-time applications. While state-of-the-art …

Abstract Automatic Speech Recognition (ASR) system is an emerging technology used in
various fields such as robotics, traffic controls, and healthcare, etc. The leading cause of …

2. RESULTS 2.1. EFFECTS OF DEVICE. Here we present the full results for the effect of
each device on the acoustic measurements. All statistical results are from mixed effects …

It remains a tough challenge to recover the speech signals contaminated by various noises
under real acoustic environments. To this end, we propose a novel system for denoising in …