Cross-lingual, Character-Level Neural Morphological Tagging
Even for common NLP tasks, sufficient supervision is not available in many languages -- morphological tagging is no exception. In the work presented here, we explore a transfer learning scheme, whereby we train character-level recurrent neural taggers to predict morphological taggings for high-resource languages and low-resource languages together. Learning joint character representations among multiple related languages successfully enables knowledge transfer from the high-resource languages to the low-resource ones, improving accuracy by up to 30% over a monolingual model.
Code (0)
등록된 구현이 없습니다.
Tasks
Morphological TaggingTransfer LearningSimilar Papers 제목 키워드 기반
Cross-lingual Character-Level Neural Morphological Tagging
Even for common NLP tasks, sufficient supervision is not available in many languages {--} morphological tagging is no exception. In the work presented here, we explore a transfer learning scheme, whereby we train charact…
Language ModelingLanguage ModellingMorphological TaggingPart-Of-Speech Tagging+1Cross-Lingual Lemmatization and Morphology Tagging with Two-Stage Multilingual BERT Fine-Tuning
We present our CHARLES-SAARLAND system for the SIGMORPHON 2019 Shared Task on Crosslinguality and Context in Morphology, in task 2, Morphological Analysis and Lemmatization in Context. We leverage the multilingual BERT m…
LemmatizationMorphological AnalysisTask 2Unsupervised Stem-based Cross-lingual Part-of-Speech Tagging for Morphologically Rich Low-Resource Languages
Unsupervised cross-lingual projection for part-of-speech (POS) tagging relies on the use of parallel data to project POS tags from a source language for which a POS tagger is available onto a target language across word-…
Part-Of-Speech TaggingPOSPOS TaggingNeural Factor Graph Models for Cross-lingual Morphological Tagging
Morphological analysis involves predicting the syntactic traits of a word (e.g. {POS: Noun, Case: Acc, Gender: Fem}). Previous work in morphological tagging improves performance for low-resource languages (LRLs) through …
Morphological AnalysisMorphological TaggingPOSTAGMultilingual Lexicalized Constituency Parsing with Word-Level Auxiliary Tasks
We introduce a constituency parser based on a bi-LSTM encoder adapted from recent work (Cross and Huang, 2016b; Kiperwasser and Goldberg, 2016), which can incorporate a lower level character biLSTM (Ballesteros et al., 2…
Constituency ParsingMorphological AnalysisMorphological TaggingPOS