Semantic 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.


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    Titel :

    Task-Oriented Semantic Communications for Speech Transmission


    Beteiligte:
    Weng, Zhenzi (Autor:in) / Qin, Zhijin (Autor:in) / Tao, Xiaoming (Autor:in)


    Erscheinungsdatum :

    10.10.2023


    Format / Umfang :

    1282515 byte





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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