---
title: "Improving Morphology Induction by Learning Spelling Rules"
authors:
  - "Jason Naradowsky"
  - "Sharon Goldwater"
doi: ""
url: "https://ijcai.org/proceedings/2009/256"
pdf: "https://ijcai.org/proceedings/2009/0256.pdf"
venue: "Proceedings of the Twenty-First International Joint Conference on Artificial Intelligence"
year: 2009
pages: "1531-1535"
track: ""
keywords:
---

# Improving Morphology Induction by Learning Spelling Rules

Jason Naradowsky, Sharon Goldwater

*Proceedings of the Twenty-First International Joint Conference on Artificial Intelligence*, pages 1531-1535.

## Abstract

Unsupervised learning of morphology is an important task for human learners and in natural language processing systems. Previous systems focus on segmenting words into substrings (taking ⇒ tak.ing), but sometimes a segmentation-only analysis is insufficient (e.g., taking may be more appropriately analyzed as take+ing, with a spelling rule accounting for the deletion of the stem-final e). In this paper, we develop a Bayesian model for simultaneously inducing both morphology and spelling rules. We show that the addition of spelling rules improves performance over the baseline morphology-only model.Jason Naradowsky, Sharon Goldwater