Cross-Lingual Keyword Search for Sign Language

Autor/a: TAMER, Nazif Can; SARACLAR, Murat
Año: 2020
Editorial: Proceedings of the 9th Workshop on the Representation and Processing of Sign Languages, pages 217–223
Tipo de código: Copyright
Soporte: Digital


Lingüística » Lingüística de otras Lenguas de Signos


Sign language research most often relies on exhaustively annotated and segmented data, which is scarce even for the most studied sign languages. However, parallel corpora consisting of sign language interpreting are rarely explored. By utilizing such data for the task of keyword search, this work aims to enable information retrieval from sign language with the queries from the translated written language. With the written language translations as labels, we train a weakly supervised keyword search model for sign language and further improve the retrieval performance with two context modeling strategies. In our experiments, we compare the gloss retrieval and cross language retrieval performance on RWTH-PHOENIX-Weather 2014T dataset.