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Language Planning as a Sociolinguistic Experiment

By: Ernst Jahr

Provides richly detailed insight into the uniqueness of the Norwegian language development. Marks the 200th anniversary of the birth of the Norwegian nation following centuries of Danish rule


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Acquiring Phonology: A Cross-Generational Case-Study

By Neil Smith

The study also highlights the constructs of current linguistic theory, arguing for distinctive features and the notion 'onset' and against some of the claims of Optimality Theory and Usage-based accounts.


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Language Production and Interpretation: Linguistics meets Cognition

By Henk Zeevat

The importance of Henk Zeevat's new monograph cannot be overstated. [...] I recommend it to anyone who combines interests in language, logic, and computation [...]. David Beaver, University of Texas at Austin


Academic Paper


Title: A novel string distance metric for ranking Persian respelling suggestions
Author: OmidKashefi
Institution: Iran University of Science and Technology
Author: MohsenSharifi
Institution: Iran University of Science and Technology
Author: BehroozMinaie
Institution: Iran University of Science and Technology
Linguistic Field: Computational Linguistics
Abstract: Spelling errors in digital documents are often caused by operational and cognitive mistakes, or by the lack of full knowledge about the language of the written documents. Computer-assisted solutions can help to detect and suggest replacements. In this paper, we present a new string distance metric for the Persian language to rank respelling suggestions of a misspelled Persian word by considering the effects of keyboard layout on typographical spelling errors as well as the homomorphic and homophonic aspects of words for orthographical misspellings. We also consider the misspellings caused by disregarded diacritics. Since the proposed string distance metric is custom-designed for the Persian language, we present the spelling aspects of the Persian language such as homomorphs, homophones, and diacritics. We then present our statistical analysis of a set of large Persian corpora to identify the causes and the types of Persian spelling errors. We show that the proposed string distance metric has a higher mean average precision and a higher mean reciprocal rank in ranking respelling candidates of Persian misspellings in comparison with other metrics such as the Hamming, Levenshtein, Damerau–Levenshtein, Wagner–Fischer, and Jaro–Winkler metrics.

CUP at LINGUIST

This article appears in Natural Language Engineering Vol. 19, Issue 2, which you can read on Cambridge's site or on LINGUIST .



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