Motivation

Traditionally linguistics has been done through intensive fieldworks and meticulous and careful analysis of data. And the only sub-field where computers and especially programming was assumed to be used was in computational linguistics (and related field of language technology, natural language processing, etc) and to certain extent in, what is called, corpus linguistics. However in the last decade or so a large amount of cutting-edge research in so-called ‘theoretical’ sub-fields of linguistics, including linguistic typology, historical linguistics, sociolinguistics, (experimental) psycholinguistics, language documentation and even linguistic descriptions of languages actually make use of fairly advanced computational processing of language data. It has become increasingly evident that in order to conduct a large amount of meaningful research in Linguistics and to start exploring some of the most interesting (empirical) questions about human language, skills in programming will prove to be an invaluable asset, if not an absolute requirement, along with the fieldwork and manual analysis. However, because of several practical constraints, barring a couple of exceptions, none of the Linguistics departments (even those departments which offer a course on computational linguistics or a related sub-field) offer a course or some kind of training in programming. This has resulted in a large number of linguists not able to make use of computer programming, even though they would like to use it for their own research. This intensive workshop series is aimed to fill this gap in the field of linguistics.

At the same time, computer programming, too, has evolved in the last few decades, resulting in the development of languages which are much closer to a human language in their structure and syntax, making them much more intuitive and hence, easier to learn and write programs in. Python has proved to be one such language which has gained immense popularity in recent times and offers excellent libraries and support from the community. A surprisingly shallow learning curve and the availability of plentiful of pre-written code to be reused by programmers of different levels and from different fields makes it an almost ideal first language to learn, especially for people from non computer science background.