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Content

Content The course introduces basic digital signal processing in the area of linguistics. It includes a theoretical part (i.e. lecture) on the knowledge required to understand how computers process digital data. It also includes a practical part in which students develop a digital solution to a task related to linguistics.

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Conditions of Participation

English proficiency on a B2 level (CEFR)

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Teaching Methods

The course applies a blended-learning concept. Students are guided through their self-study time by means of a structured online course (in the Moodle Learning Management System). The competences acquired in the online course help students achieve the implementation tasks covered in the practical part of the course which are developed as synchronous group work sessions assisted by the lecturer.

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Learning outcomes / Competences

Upon completion of the module, students will have a basic understanding on the digital processes involved in processing language-related data and convert it into useful information by means of automation.

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Forms of examination

Online assessment of competencies and learning diary

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Conditions for allocation of credit points

Workload: Successful course participation (i.e. completion of at least 80% of online course contents), submission of learning diary and successful completion of online assessment (at least 60% correct answers)

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Other information

Individual topics covered in the lecture: data collection methods, conversion of analogue into digital data, basic statistical methods (descriptive and inferential), basic machine learning algorithms, HTML5