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• W3087091162 abstract "End-to-end speech-to-text translation (ST), which directly translates the source language speech to the target language text, has attracted intensive attention recently. However, the combination of speech recognition and machine translation in a single model poses a heavy burden on the direct cross-modal cross-lingual mapping. To reduce the learning difficulty, we propose SDST, an integral framework with textbf{S}uccessive textbf{D}ecoding for end-to-end textbf{S}peech-to-text textbf{T}ranslation task. This method is verified in two mainstream datasets. Experiments show that our proposed method improves the previous state-of-the-art methods by big margins." @default.
• W3087091162 created "2020-09-25" @default.
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• W3087091162 date "2020-09-21" @default.
• W3087091162 modified "2023-09-27" @default.
• W3087091162 title "SDST: Successive Decoding for Speech-to-text Translation." @default.
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• W3087091162 hasPublicationYear "2020" @default.
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