Course Catalog 2012-2013
Postgraduate

Basic Pori International Postgraduate Open University

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Course Catalog 2012-2013

SGN-4106 Speech Recognition, 5 cr

Additional information

Suitable for postgraduate studies

Person responsible

Tuomas Virtanen, Jani Nurminen, Annamaria Mesaros

Lessons

Study type P1 P2 P3 P4 Summer Implementations Lecture times and places
Lectures
Excercises


 


 


 
 4 h/week
 2 h/week


 
SGN-4106 2012-01 Tuesday 14 - 16, TB222
Wednesday 12 - 14, TB223

Requirements

Final examination and exercises.

Principles and baselines related to teaching and learning

-

Learning outcomes

After completing this course, the student will understand the basic techniques used in speech recognition. He or she will be able to implement the front-end used for extracting relevant information from the speech signal. The student will have a detailed understanding of the mathematical principles of hidden Markov models (HMMs) that are used to model the data provided courtesy of the front-end. The student will be able to calculate quantities that are requred to train HMMs and use them for pattern classification. The student will be able to implement a simple HMM-based speech recognition system.

Content

Content Core content Complementary knowledge Specialist knowledge
1. Front-end of a speech recognizer, cepstral coefficients, phonetics     
2. Hidden Markov models: training the models and using them for pattern classification.     
3. The use of hidden Markov models for automatic speech recognition.      
4. Language models     

Evaluation criteria for the course

Exam and exercises. Excellent grade can be obtained by answering to the questions in an exam by the extent the topic have been dealth with on the lectures and exercises. Approximately half of the maximum number of points need to be obtained and 20% of the exercises need to be completed in order to pass the course.

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
Lecture slides     Bryan Pellom            English  

Prerequisites

Course Mandatory/Advisable Description
SGN-2500 Johdatus hahmontunnistukseen Advisable   1
SGN-2506 Introduction to Pattern Recognition Advisable   1
SGN-4010 Puheenkäsittelyn menetelmät Mandatory    

1 . Prior knowledge about pattern recognition is advisable.

Additional information about prerequisites
SGN-4010 Speech Processing or corresponding knowledge of speech processing is required.

Prerequisite relations (Requires logging in to POP)



Correspondence of content

Course Corresponds course  Description 
SGN-4106 Speech Recognition, 5 cr 8003163 Speech Recognition, 3 cu  
SGN-4106 Speech Recognition, 5 cr +
SGN-4227 Digital Audio Processing and Analysis, 6 cr
SGN-24006 Analysis of Audio, Speech and Music Signals, 5 cr  

More precise information per implementation

Implementation Description Methods of instruction Implementation
SGN-4106 2012-01        

Last modified12.03.2013