2013
DOI: 10.1007/978-3-319-03524-6_17
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Deep Natural Language Processing for Italian Sign Language Translation

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Cited by 27 publications
(7 citation statements)
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“…The project approach relies on the experience, knowledge, and resources of the previous ATLAS project [10], a pioneering project on the automatic translation from Italian into LIS that set up the complete pipeline and focused on the weather forecasting domain. The LIS4ALL project extends the coverage of syntactic constructions and the lexicon built for ATLAS (about 2350 signs), by adding the signs that are specific to the railway domain (about 120).…”
Section: The Architecture Of Lis4allmentioning
confidence: 99%
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“…The project approach relies on the experience, knowledge, and resources of the previous ATLAS project [10], a pioneering project on the automatic translation from Italian into LIS that set up the complete pipeline and focused on the weather forecasting domain. The LIS4ALL project extends the coverage of syntactic constructions and the lexicon built for ATLAS (about 2350 signs), by adding the signs that are specific to the railway domain (about 120).…”
Section: The Architecture Of Lis4allmentioning
confidence: 99%
“…The output of the microplanner is a hybrid logic formula in a tree structure (XML), that encodes an abstract syntactic tree. Extending the Combinatory Categorical Grammar (CCG) grammar [18] designed in the ATLAS project [10] and using the parallel Italian-LIS corpus produced in LIS4ALL, we implemented a new CCG grammar for LIS that can be used by the OpenCCG realizer to produce LIS sentences in the railway domain [19]. The output of the realizer is an XML file specified with the AWLIS (Atlas Written LIS) language, i.e., a sequence of lemmata, accompanied by a description of the meaning of each lemma, its syntactic number and the link to the corresponding sign.…”
Section: The Architecture Of Lis4allmentioning
confidence: 99%
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“…However, the symbolic approach we implemented produces the structure of the sentence in the target language. This information is used for the automatic allocation of the signs in the signing space for LIS (Mazzei et al 2013), an aspect not yet implemented in current statistical approaches. LIS4ALL only uses the symbolic (rule-based) translation architecture to process the Italian input and generate the final LIS string.…”
mentioning
confidence: 99%
“…The project is the prosecution of ATLAS, a project of automatic translation into LIS of weather forecasting (http://www.atlas.polito.it/index.php/en). In ATLAS two distinct approaches to automatic translation have been adopted, interlingua rule-based translation and statistical translation (Mazzei et al 2013, Tiotto et al, 2010, Hutchins and Somer 1992. Both approaches have advantages and drawbacks in the specific context of automatic translation into SL.…”
mentioning
confidence: 99%