LEARNING OUTCOMES
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.
Credits: 5
Schedule: 23.10.2024 - 05.12.2024
Teacher in charge (valid for whole curriculum period):
Teacher in charge (applies in this implementation): Mikko Kurimo
Contact information for the course (applies in this implementation):
CEFR level (valid for whole curriculum period):
Language of instruction and studies (applies in this implementation):
Teaching language: English. Languages of study attainment: English
CONTENT, ASSESSMENT AND WORKLOAD
Content
valid for whole curriculum period:
Preprocessing and feature extraction for speech, phoneme models,
decoding, lexicon and language models, recognition and applications of
continuous speech.
Assessment Methods and Criteria
valid for whole curriculum period:
Exercises and project work.
Workload
valid for whole curriculum period:
Lectures
Home exercises, group projects, and other individual work
DETAILS
Study Material
valid for whole curriculum period:
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
valid for whole curriculum period:
Prerequisites
valid for whole curriculum period:
SDG: Sustainable Development Goals
3 Good Health and Well-being
4 Quality Education
5 Gender Equality
9 Industry, Innovation and Infrastructure
10 Reduced Inequality
FURTHER INFORMATION
Further Information
valid for whole curriculum period:
Teaching Language: English
Teaching Period: 2024-2025 Autumn II
2025-2026 Autumn II