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  1. Home
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  3. Similar Languages, Varieties, and Dialects
  • Cited by 6
Publisher:
Cambridge University Press
Online publication date:
August 2021
Print publication year:
2021
Online ISBN:
9781108565080
DOI:
https://doi.org/10.1017/9781108565080
Series:
Studies in Natural Language Processing
Subjects:
Computational Linguistics, Computer Science, Artificial Intelligence and Natural Language Processing, Language and Linguistics
Information

Book description

Language resources and computational models are becoming increasingly important for the study of language variation. A main challenge of this interdisciplinary field is that linguistics researchers may not be familiar with these helpful computational tools and many NLP researchers are often not familiar with language variation phenomena. This essential reference introduces researchers to the necessary computational models for processing similar languages, varieties, and dialects. In this book, leading experts tackle the inherent challenges of the field by balancing a thorough discussion of the theoretical background with a meaningful overview of state-of-the-art language technology. The book can be used in a graduate course, or as a supplementary text for courses on language variation, dialectology, and sociolinguistics or on computational linguistics and NLP. Part 1 covers the linguistic fundamentals of the field such as the question of status and language variation. Part 2 discusses data collection and pre-processing methods. Finally, Part 3 presents NLP applications such as speech processing, machine translation, and language-specific issues in Arabic and Chinese.

Reviews

‘Variation is a key aspect of human language, and yet it has been too often overlooked in computational linguistics. The book edited by Marcos Zampieri and Preslav Nakov is an important step towards filling this gap with top-level contributions that offer a new alliance between natural language processing and linguistic theory to understand this complex phenomenon and its impact on applications.'

Alessandro Lenci - University of Pisa

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