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Found 5 papers, 2 papers with code
Robust Semantic Communications for Speech-to-Text Translation
Moreover, to cope with the practical communication scenario when the input speech is corrupted, a novel generative adversarial network (GAN)-enabled deep semantic compensator is proposed to predict the lost semantic information in the source speech and produce the textual semantic features in the target language simultaneously, which establishes a robust semantic transmission mechanism for dynamic speech input.
Generative Adversarial Network
Speech-to-Text Translation
+1
Deep Learning Enabled Semantic Communications with Speech Recognition and Synthesis
In this paper, we develop a deep learning based semantic communication system for speech transmission, named DeepSC-ST. We take the speech recognition and speech synthesis as the transmission tasks of the communication system, respectively.
Semantic Communications for Speech Recognition
The traditional communications transmit all the source date represented by bits, regardless of the content of source and the semantic information required by the receiver.
Semantic Communication Systems for Speech Transmission
In order to improve the recovery accuracy of speech signals, especially for the essential information, DeepSC-S is developed based on an attention mechanism by utilizing a squeeze-and-excitation (SE) network.
Semantic Communications for Speech Signals
We consider a semantic communication system for speech signals, named DeepSC-S.
