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.

CORILSE is a computerized corpus of Spanish Sign Language (Lengua de Signos Española, LSE). It consists of a set of recordings from different discourse genres by Galician signers living in the city of Vigo. In this paper we describe its annotation system, developed on the basis of pre-existing ones (mostly the model of Auslan corpus). This includes primary annotation of id-glosses for manual signs, annotation of non-manual component, and secondary annotation of grammatical categories and relations, because this corpus is been built for grammatical analysis, in particular argument structures in LSE. Up until this moment the annotation has been basically made by hand, which is a slow and time-consuming task. The need to facilitate this process leads us to engage in the development of automatic or semi-automatic tools for manual and facial recognition. Finally, we also present the web repository that will make the corpus available to different types of users, and will allow its exploitation for research purposes and other applications (e.g. teaching of LSE or design of tasks for signed language assessment).