Paper: Large tagset labeling using Feed Forward Neural Networks. Case study on Romanian Language

ACL ID P13-1068
Title Large tagset labeling using Feed Forward Neural Networks. Case study on Romanian Language
Venue Annual Meeting of the Association of Computational Linguistics
Session Main Conference
Year 2013
Authors

Standard methods for part-of-speech tagging suffer from data sparseness when used on highly inflectional languages (which require large lexical tagset inventories). For this reason, a number of alternative methods have been proposed over the years. One of the most successful methods used for this task, FDOOHG7LHUHG7DJJLQJ 7XIL, 1999), exploits a reduced set of tags derived by removing several recoverable features from the lexicon morpho-syntactic descriptions. A second phase is aimed at recovering the full set of morpho-syntactic features. In this paper we present an alternative method to Tiered Tagging, based on local optimizations with Neural Networks and we show how, by properly encoding the input sequence in a general Neural Network architecture, we achieve result...