Course Catalog 2009-2010 International Basic Pori International Postgraduate Open University |Degrees|     |Study blocks|     |Courses|

Person responsible

Konsta Koppinen

Implementations

No implementations

Requirements

Final examination and exercises.

Principles and baselines related to teaching and learning

-

Learning outcomes

Teaches the basics of automated speech recognition, particularly the use of hidden Markov models and neural networks.

Content

Content	Core content	Complementary knowledge	Specialist knowledge
1.	Front-end of a speech recognizer, cepstral coefficients
2.	Training of Hidden Markov models (HMM)
3.	Adaptation methods
4.	Language models

Evaluation criteria for the course

Exam and exercises.

Assessment scale:

Numerical evaluation scale (1-5) will be used on the course

Study material

Type	Name	Author	ISBN	URL	Edition, availability, ...	Examination material	Language
Book	"Automatic Speech and Speaker Recognition-Advanced Topics"	Lee, C.H.,Soong, F.K.,Paliwal,K.K.			Kluwer Academic Publishers, 1996		English
Book	"Fundamentals of Speech Recognition"	Rabiner, L. & Juang, B-H.			Prentice Hall, 1993		English
Book	"Neural Networks - Second Edition"	Haykin, S.			Prentice Hall, 1999		English
Book	"Pattern Classification"	Duda, R.O., Hart, P.E. & Stork, D.G.			Wiley, 2000		English
Book	"Robust Speech Recognition in Embedded Systems and PC Applications"	Junqua, J.C.			Kluwer Academic Publishers, 2000		English
Book	Spoken language processing	Huang, Acero, Hsiao-Wuen Hon					English
Journal	"A tutorial on hidden Markov models and selected applications in speech recognition"	Rabiner, L.R.			Proceedings of the IEEE , Volume: 77 Issue: 2 , Feb. 1989		Suomi
Journal	"Statistical Pattern Recognition: A Review"	Jain, Duin, Mao			IEEE Trans. Pattern Analysis and Machine Intelligence, Vol. 22, No. 1, Jan. 2000		English
Lecture slides	"Speech Recognition"	Konsta Koppinen					English

Prerequisites

Correspondence of content

Last modified	16.06.2009
Modifier	Konsta Koppinen