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DT2112 Speech Technology 7.5 credits

Administer About course

The central part of the course concerns how speech can be used in human-computer interaction. Applications such as speaking and speech-understanding computers and multimodal dialogue systems are presented, such as applying machine learning techniques to train models for recognizing speech patterns and speaker characteristics. The course describes the basic human communication concepts regarding speech, language and hearing. The use of digital signal analysis and statistical methods for analysing and classifying speech are also addressed, as are the evaluation, research and development of speech technology methods.

Information per course offering

Choose semester and course offering to see current information and more about the course, such as course syllabus, study period, and application information.

Termin

Course syllabus as PDF

Please note: all information from the Course syllabus is available on this page in an accessible format.

Course syllabus DT2112 (Autumn 2021–)
Headings with content from the Course syllabus DT2112 (Autumn 2021–) are denoted with an asterisk ( )

Content and learning outcomes

Course contents

The course Speech Technology deals with research and development in speech technology and also povides basic insights in speech, language and hearing. The course contains segments concerning:

  • Linguistic theory and phonetics
  • Speech production by humans (speech physiology and acoustics) and computers (text-to-speech synthesis)
  • Speech perception by humans (hearing and psycholinguistics) and computers (speech recognition)
  • Multimodal dialogue systems for human-computer interaction with speech and vision
  • Practical speech technology studies and experiments
  • Methods for evaluation of and experimentation in speech technology
  • Data collection for speech technology research and development

Intended learning outcomes

After completion of the course, participants shall be able to:

  • Describe speech from an acoustic, phonetic, and linguistic perspective
  • Explain how computers recognize speech with statistical methods, and evaluate the recognition results
  • Describe and judge different methods used to produce speech with computers
  • Analyze speech-driven dialogue systems with respect to application, components, functionality and user aspects
  • Describe how evaluation of speech technology systems work and describe the special requirements that are posed by this type of system
  • Design and describe data collections for speech technology research and development
  • Give an account of available state-of-the art speech technology and exemplify the current speech research on e.g., mobile systems and IT applications
  • Apply the theoretical knowledge in small speech technology projects

Literature and preparations

Specific prerequisites

Single course students: At least 60 ECTS of which 30 ECTS within Mathematics or Computational Lingvistics. Furthermore English B, or equivalent.

Recommended prerequisites

Proficiency in mathematics and signal analysis corresponding to the first 2.5 years of Degree Programme in Media Technology.

Equipment

No information inserted

Literature

No information inserted

Examination and completion

If the course is discontinued, students may request to be examined during the following two academic years.

Grading scale

A, B, C, D, E, FX, F

Examination

  • LABA - Laboratory assignments, 0.5 credits, grading scale: P, F
  • LABB - Research laboratory assignment, - credits, grading scale: A, B, C, D, E, FX, F
  • PR01 - Project and report, 3.5 credits, grading scale: A, B, C, D, E, FX, F
  • TENA - Home exam, 3.5 credits, grading scale: A, B, C, D, E, FX, F

Based on recommendation from KTH’s coordinator for disabilities, the examiner will decide how to adapt an examination for students with documented disability.

The examiner may apply another examination format when re-examining individual students.

Other requirements for final grade

  • Active participation in scheduled activities
  • Pass on labs (timely)
  • Pass on project bid (timely)
  • Pass on project presentation (timely)
  • E or better on project report (A-E, decides 50% of end grade)
  • E or better on home exam (A-E, decides 50% of the end grade)

Pass on labs, project bid, and project presentation are necessary in order to continue the course. Late hand-in of home exam or project report results a grade lowering (one step). One reexam is given, with a limited range of passed grades (B-E).

Opportunity to complete the requirements via supplementary examination

No information inserted

Opportunity to raise an approved grade via renewed examination

No information inserted

Examiner

Profile picture Joakim Gustafsson

Profile picture Jens Edlund

Ethical approach

  • All members of a group are responsible for the group's work.
  • In any assessment, every student shall honestly disclose any help received and sources used.
  • In an oral assessment, every student shall be able to present and answer questions about the entire assignment and solution.

Further information

Course room in Canvas

Registered students find further information about the implementation of the course in the course room in Canvas. A link to the course room can be found under the tab Studies in the Personal menu at the start of the course.

Offered by

EECS/Intelligent Systems

Main field of study

Electrical Engineering

Education cycle

Second cycle

Add-on studies

No information inserted

Contact

Jens Edlund, e-post: edlund@speech.kth.se

Supplementary information

In this course, the EECS code of honor applies, see:
http://www.kth.se/en/eecs/utbildning/hederskodex