Computational Modelling (Prof. Kevin Tang, WiSe 2023/24, Wed: 14:30--16:00)

**Description:**

Natural Language Processing plays a big role in our digital lives. We will demystify some of these everyday tasks that involve natural language processing: such as spelling and grammar correction, document classification, dialogue systems, machine translation, and forensic linguistics. On the practical side, we will focus on applying off-the-shelf tools that are often used in computational modelling of language data. Armed with these skills, you will be able to model language data quantitatively and ask measurable research questions.


By the end of the course, you will learn how to perform i) pre-processing of text files (cleaning up raw text files), ii) automatic linguistic annotation, such as Part of Speech tagging (automatically adding labels such as Noun, Adjective to each word), Name Entity Recognition (identifying proper names, time, date, places, events) and Sentiment (fear, anger, happy, surprise…) iii) the basics of classifying documents, authors and sentiment.
 

Students will get insight into how these systems work (and why it is still so difficult to do natural language processing well). We also consider social and ethical considerations such as privacy, job creation and loss due to language technologies, and the nature of consciousness and machine intelligence.

For more information on LSF: https://lsf.hhu.de/qisserver/rds?state=verpublish&status=init&vmfile=no&publishid=245927&moduleCall=webInfo&publishConfFile=webInfo&publishSubDir=veranstaltung