We consider the wireless text transmission using joint source-channel coding (JSCC).
Classical source coding only considers the syntactic information based on probabilistic …

Semantic communications is considered a promising technology that will increase the
efficiency of next-generation communication systems, particularly human-machine and …

We consider joint source and channel coding of natural language over a noisy channel
using deep learning. While the typical approach based on separate source and channel …

As a promising technology to enable effective multi-modal transmission over wireless
channels, semantic communication has attracted a lot of attention from academics and …

Recently, semantic communication has been brought to the forefront because deep learning
(DL)-based methods, such as Transformer, have achieved great success in semantic …

In this paper, we propose a class of high-efficiency deep joint source-channel coding
methods that can closely adapt to the source distribution under the nonlinear transform, it …

Semantic communication systems have been proposed for efficient text transmissions in
recent years. However, most existing methods mainly focus on word-level recovery, which …

We consider the problem of joint source and channel coding of structured data such as
natural language over a noisy channel. The typical approach to this problem in both theory …

Increasing research has focused on semantic communication, the goal of which is to convey
accurately the meaning instead of transmitting symbols from the sender to the receiver. In …

In this paper, we propose a new class of high-efficiency semantic coded transmission
methods to realize end-to-end speech transmission over wireless channels. We name the …