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dc.contributor.authorWeng, Z
dc.contributor.authorQin, Z
dc.contributor.authorTao, X
dc.date.accessioned2024-06-07T08:47:24Z
dc.date.available2024-06-07T08:47:24Z
dc.date.issued2023-01-01
dc.identifier.isbn9798350329285
dc.identifier.issn1550-2252
dc.identifier.urihttps://qmro.qmul.ac.uk/xmlui/handle/123456789/97333
dc.description.abstractSemantic communications execute intelligent tasks at the receiver by only transmitting necessary information. In this paper, we introduce TOS-ST, a task-oriented semantic communication system for speech transmission, which efficiently serves the semantic tasks at the receiver, including speech-to-text translation and speech-to-speech translation. Particularly, TOS-ST condenses the input speech in the source language and extracts the task-related semantics features prior to transmission. At the receiver, these features are recovered and utilized by the neural network-based semantic preserver and machine translation module to generate the uncorrupted text in the target language. To perform the speech-to-speech translation task, the translated text passes through a sophisticated neural network to obtain speech in the target language. According to the simulation results, the TOS-ST outperforms conventional speech transmission systems and exhibits higher robustness against channel impairment.en_US
dc.publisherIEEEen_US
dc.titleTask-Oriented Semantic Communications for Speech Transmissionen_US
dc.typeConference Proceedingen_US
dc.rights.holder© 2023 IEEE.
dc.identifier.doi10.1109/VTC2023-Fall60731.2023.10333632
pubs.notesNot knownen_US
pubs.publication-statusPublisheden_US
rioxxterms.funderDefault funderen_US
rioxxterms.identifier.projectDefault projecten_US


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