Please note! Course description is confirmed for two academic years (1.8.2018-31.7.2020), which means that in general, e.g. Learning outcomes, assessment methods and key content stays unchanged. However, via course syllabus, it is possible to specify or change the course execution in each realization of the course, such as how the contact sessions are organized, assessment methods weighted or materials used.
To become familiar with speech recognition methods and applications. Additionally, to learn to understand the structure of a typical speech recognition system and to know how to construct one in practice.
Schedule: 28.10.2020 - 11.12.2020
Teacher in charge (valid 01.08.2020-31.07.2022): Paavo Alku, Mikko Kurimo
Teacher in charge (applies in this implementation): Mikko Kurimo
Contact information for the course (applies in this implementation):
CEFR level (applies in this implementation):
Language of instruction and studies (valid 01.08.2020-31.07.2022):
Teaching language: English
Languages of study attainment: English
CONTENT, ASSESSMENT AND WORKLOAD
Preprocessing and feature extraction for speech, phoneme models,
decoding, lexicon and language models, recognition and applications of
Assessment Methods and Criteria
Exercises and project work.
Home exercises, group projects, and other individual work: 109 h
Attendance in some contact teaching may be compulsory.
Huang, Acero: Spoken Language Processing. Prentice Hall, 2001 ISBN: 0-13-022616-5
Yu, Deng: Automatic Speech Recognition A Deep Learning Approach. Springer, 2015 ISBN: 978-1-4471-5779-3
Substitutes for Courses
Basic mathematics and probability courses.
SDG: Sustainable Development Goals
9 Industry, Innovation and Infrastructure
- Teacher: Mikko Kurimo