DIGITAL TOOLS FOR LINGUISTICS
The field of linguistics draws heavily on computational approaches and is a field where programming skills and high levels of technical expertise are common. Broadly speaking, early work in the field centred on the problems of natural language processing and the development of techniques to enable sophisticated human-machine interaction in a variety of ways. A significant amount of work was carried out to try and make progress in areas such as machine translation, speech recognition and automated question/answer systems (artificial intelligence) and a lot of this work was based on advances made in information theory by figures such as Claude Shannon who as early as 1948 wrote the influential paper, ‘A Mathematical Theory of Communication’.
The long-established relationship between Computer Science and Linguistics is indicative of the centrality of digital tools development to the discipline and as a result, there is a prodigious amount of software available to researchers to carry out a wide variety of sometimes quite specific functions. Scholars engaging with linguistics have no choice but to embrace digital tools because their research is often predicated on the detailed and quantitative analysis of large amounts of digitized text. However, one of the unifying conclusions to many articles and essays concerning the subject is that quantitative research methods have to be mediated with qualitative analysis. As Marilyn Deegan states in her rapporteur’s report relating to the Methods Network expert seminar on linguistics, ‘there is no such thing as bias-free research or intuition-free linguistics’.
Read the full Working Paper: (pdf)
http://www.methodsnetwork.ac.uk/redist/pdf/wkp03.pdf
The field of linguistics draws heavily on computational approaches and is a field where programming skills and high levels of technical expertise are common. Broadly speaking, early work in the field centred on the problems of natural language processing and the development of techniques to enable sophisticated human-machine interaction in a variety of ways. A significant amount of work was carried out to try and make progress in areas such as machine translation, speech recognition and automated question/answer systems (artificial intelligence) and a lot of this work was based on advances made in information theory by figures such as Claude Shannon who as early as 1948 wrote the influential paper, ‘A Mathematical Theory of Communication’.
The long-established relationship between Computer Science and Linguistics is indicative of the centrality of digital tools development to the discipline and as a result, there is a prodigious amount of software available to researchers to carry out a wide variety of sometimes quite specific functions. Scholars engaging with linguistics have no choice but to embrace digital tools because their research is often predicated on the detailed and quantitative analysis of large amounts of digitized text. However, one of the unifying conclusions to many articles and essays concerning the subject is that quantitative research methods have to be mediated with qualitative analysis. As Marilyn Deegan states in her rapporteur’s report relating to the Methods Network expert seminar on linguistics, ‘there is no such thing as bias-free research or intuition-free linguistics’.
Read the full Working Paper: (pdf)
http://www.methodsnetwork.ac.uk/redist/pdf/wkp03.pdf
