2026-08-15T22:59:50Z https://drops.dagstuhl.de/oai

oai:drops-oai.dagstuhl.de:4574 2024-03-06T10:29:31Z ddc:004 open_access

Language Identification: a Neural Network Approach Simões, Alberto Almeida, José João Byers, Simon D. language identification neural networks language models trigrams One of the first tasks when building a Natural Language application is the detection of the used language in order to adapt the system to that language. This task has been addressed several times. Nevertheless most of these attempts were performed a long time ago when the amount of computer data and the computational power were limited. In this article we analyze and explain the use of a neural network for language identification, where features can be extracted automatically, and therefore, easy to adapt to new languages. In our experiments we got some surprises, namely with the two Chinese variants, whose forced us for some language-dependent tweaking of the neural network. At the end, the network had a precision of 95%, only failing for the Portuguese language. Schloss Dagstuhl – Leibniz-Zentrum für Informatik Alberto Simões and José João Almeida and Simon D. Byers 2014 Is Part Of OASIcs, Volume 38, 3rd Symposium on Languages, Applications and Technologies (2014) InProceedings Text doc-type:ResearchArticle publishedVersion application/pdf doi:10.4230/OASIcs.SLATE.2014.251 urn:nbn:de:0030-drops-45749 https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.SLATE.2014.251 eng https://creativecommons.org/licenses/by/3.0/legalcode