With the increasing demand for intelligent services, the sixth-generation (6G) wireless
networks will shift from a traditional architecture that focuses solely on a high transmission …

In this study, we present recent developments on ESPnet: End-to-End Speech Processing
toolkit, which mainly involves a recently proposed architecture called Conformer …

SpeechBrain is an open-source and all-in-one speech toolkit. It is designed to facilitate the
research and development of neural speech processing technologies by being simple …

Semantic communications could improve the transmission efficiency significantly by
exploring the semantic information. In this paper, we make an effort to recover the …

Recurrent Neural Networks (RNNs) have long been the dominant architecture in sequence-
to-sequence learning. RNNs, however, are inherently sequential models that do not allow …

Recent studies in deep learning-based speech separation have proven the superiority of
time-domain approaches to conventional time-frequency-based methods. Unlike the time …

We present and release a new tool for music source separation with pre-trained models
called Spleeter. Spleeter was designed with ease of use, separation performance, and …

In speech enhancement and source separation, signal-to-noise ratio is a ubiquitous
objective measure of denoising/separation quality. A decade ago, the BSS_eval toolkit was …

Single-channel, speaker-independent speech separation methods have recently seen great
progress. However, the accuracy, latency, and computational cost of such methods remain …

Given the recent surge in developments of deep learning, this paper provides a review of the
state-of-the-art deep learning techniques for audio signal processing. Speech, music, and …