Toward a Lightweight Solution for Less-resourced Languages: Creating a POS Tagger for Alsatian Using Voluntary Crowdsourcing

Abstract

We present here the results of an experiment aiming at crowdsourcing part-of-speech annotations for a less-resourced French regional language, Alsatian. We used for this purpose a specifically-developed slightly gamified platform, Bisame. It allowed us to gather annotations on a variety of corpora covering some of the language dialectal variations. The quality of the annotations, which reach an averaged F-measure of 93%, enabled us to train a first tagger for Alsatian that is nearly 84% accurate. The platform as well as the produced annotations and tagger are freely available. The platform can easily be adapted to other languages, thus providing a solution to (some of) the less-resourced languages issue.

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