nlp:morphological_analysis
Table of Contents
Morphological Analysis
Overviews
- Morphological analysis with FSTs: Speech and Language Processing 2nd Ed, Ch 3
- Lecture: NLP 201 - Fall 2020 Oct 15
- Related work of Chahuneau 2013 (section 6) gives a very quick overview
Unsupervised Analysers
- Goldwater et al 2005 - Interpolating Between Types and Tokens by Estimating Power-Law Generators “We show that taking a particular stochastic process – the Pitman-Yor process – as an adaptor justifies the appearance of type frequencies in formal analyses of natural language, and improves the performance of a model for unsupervised learning of morphology.”
- Chahuneau et al 2013 - Knowledge-Rich Morphological Priors for Bayesian Language Models Combines a finite-state guesser (that was constructed in 3 hours) with Bayesian non-parametrics to learn the correct morphological analysis. Limitation: assumes each word has one best morphological analysis, taken out of context. This could be corrected with contextualized model, like a sequence model for the part-of-speech tags
Neural Analysers
Finite-State Analysers
- Software
- Tutorials
- Papers
People
Related Pages
nlp/morphological_analysis.txt · Last modified: 2023/06/15 07:36 by 127.0.0.1