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- W3135477360 abstract "Sign language, the main mode of communication for the Deaf, is different from the written language in terms of both vocabulary and grammar. Lacking a proper written form, information retrieval from this visual language is a challenging task. Keyword search for sign language will benefit greatly from the use of written language text queries by (i) creating a middle ground for information retrieval, (ii) enabling the people outside of the Deaf community to learn sign language and (iii) making vast amount of parallel corpora between sign language and the written language available for research. In this work, we propose a cross-lingual keyword search paradigm for sign language based on neural machine translation, and analyze the effects of different decoding strategies on retrieval performance." @default.
- W3135477360 created "2021-03-15" @default.
- W3135477360 creator A5041283771 @default.
- W3135477360 creator A5055086464 @default.
- W3135477360 date "2020-10-05" @default.
- W3135477360 modified "2023-10-18" @default.
- W3135477360 title "Keyword Search for Sign Language using Machine Translation" @default.
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- W3135477360 doi "https://doi.org/10.1109/siu49456.2020.9302337" @default.
- W3135477360 hasPublicationYear "2020" @default.
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