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--- nlp:morphological_analysis [2021/10/04 04:34] – [Unsupervised Analysers] jmflanig
+++ nlp:morphological_analysis [2023/06/15 07:36] (current) – external edit 127.0.0.1
@@ Line 7: / Line 7: @@
 ===== Unsupervised Analysers =====
+  * [[https://proceedings.neurips.cc/paper/2005/file/4b21cf96d4cf612f239a6c322b10c8fe-Paper.pdf|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."
   * [[https://aclanthology.org/N13-1140.pdf|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
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 ===== Finite-State Analysers =====
-  * [[https://www.aclweb.org/anthology/2020.lrec-1.326.pdf|Chen et al 2020 - Improved Finite-State Morphological Analysis for St. Lawrence Island Yupik Using Paradigm Function Morphology]]
+  * Software
+    * [[https://fomafst.github.io/|Foma]]
+  * Tutorials
+    * [[https://fomafst.github.io/morphtut.html|Tutorial - Building a Finite-State Morphological Analyzer]]
+  * Papers
+    * [[https://www.aclweb.org/anthology/2020.lrec-1.326.pdf|Chen et al 2020 - Improved Finite-State Morphological Analysis for St. Lawrence Island Yupik Using Paradigm Function Morphology]]
 ===== People =====
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 ===== Related Pages =====
   * [[FSAs and FSTs]]
+  * [[linguistics:Morphology]]