F20CA Conversational Agents and Spoken Language Processing

Prof Oliver LemonDr Verena Rieser

Course co-ordinator(s): Prof Oliver Lemon (Edinburgh), Dr Verena Rieser (Edinburgh).


This course aims to give students the opportunity to develop:

  • Knowledge and understanding of design, implementation and evaluation techniques for conversational agents and spoken language processing.
  • An awareness of current research and emerging issues in the field of conversational agents and spoken language processing.
  • Knowledge that covers a range of interdisciplinary research methods and specialised practical skills involved in building working conversational interfaces.

Detailed Information

Course Description: Link to Official Course Descriptor.

Pre-requisite course(s): F29AI Artificial Intelligence and Intelligent Agents or equivalent. Programming skills..

Location: Edinburgh.

Semester: 2.


This course covers current and emerging topics in conversational agents, spoken language processing, and multimodal interfaces, including:

  • Introduction to research areas, such as spoken dialogue systems, multi-modal interaction, natural language processing, and human robot interaction.
  • Spoken input processing and interpretation.
  • Interaction Management.
  • Output generation, multimodal fission, speech and gesture synthesis
  • System development and evaluation.

Learning Outcomes: Subject Mastery

Understanding, Knowledge and Cognitive Skills Scholarship, Enquiry and Research (Research-Informed Learning)

  • Knowledge and understanding of how to review, critically analyse, evaluate and synthesize previous research in the field of conversational agents and spoken language processing.
  • Use of current technologies.
  • Acquire knowledge in applying algorithmic and interdisciplinary methods on conversational interfaces.
  • Make informed judgments about appropriate methodologies for developing and evaluating conversational interfaces.
  • Practice in implementing conversational interfaces using a suitable programming language and software tools.
  • Experience in the use of multimodal sensors and existing Natural Language Processing technologies.

Learning Outcomes: Personal Abilities

Industrial, Commercial & Professional Practice Autonomy, Accountability & Working with Others Communication, Numeracy & ICT

  • Identification, representation and solution of problems.
  • Time management and resource organisation.
  • Research skills and report writing.
  • Practise in the use of ICT, numeracy and presentation skills.
  • Experience in group work: Take responsibility for their own and other’s work by contributing effectively and conscientiously to the work of a group, actively maintaining, good working relationships with group members, and leading the direction of the group where appropriate.

Assessment Methods:

Assessment: Coursework 1 Presentation : (weighting – 20%) Coursework 2 Demo : (weighting – 20%) Written report (weighting – 60%)
Re-assessment: None

SCQF Level: 10.

Credits: 15.