This paper proposes utilizing a unified speech- Textual content illustration learning framework to overcome the shortage of parallel speech-textual content datasets during the S2TT system and achieves aggressive results compared with other point out-of-the-artwork styles in CoVoST two dataset and supplies important improvement while in the tougher
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