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LSE\_UVIGO: A Multi-source Database for Spanish Sign Language Recognition

2020-05-01 · LREC 2020 5 · Laura Doc{\'\i}o-Fern{\'a}ndez, Jos{\'e} Luis Alba-Castro, Soledad Torres-Guijarro, Eduardo Rodr{\'\i}guez-Banga, Manuel Rey-Area, Ania P{\'e}rez-P{\'e}rez, Sonia Rico-Alonso, Carmen Garc{\'\i}a-Mateo

This paper presents LSE{\_}UVIGO, a multi-source database designed to foster research on Sign Language Recognition. It is being recorded and compiled for Spanish Sign Language (LSE acronym in Spanish) and contains also spoken Galician language, so it is very well fitted to research on these languages, but also quite useful for fundamental research in any other sign language. LSE{\_}UVIGO is composed of two datasets: LSE{\_}Lex40{\_}UVIGO, a multi-sensor and multi-signer dataset acquired from scratch, designed as an incremental dataset, both in complexity of the visual content and in the variety of signers. It contains static and co-articulated sign recordings, fingerspelled and gloss-based isolated words, and sentences. Its acquisition is done in a controlled lab environment in order to obtain good quality videos with sharp video frames and RGB and depth information, making them suitable to try different approaches to automatic recognition. The second subset, LSE{\_}TVGWeather{\_}UVIGO is being populated from the regional television weather forecasts interpreted to LSE, as a faster way to acquire high quality, continuous LSE recordings with a domain-restricted vocabulary and with a correspondence to spoken sentences.

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Sign Language Recognition

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