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Course Catalog 2011-2012
SGN-4507 Speech Recognition Laboratory, 3 cr |
Additional information
Suitable for postgraduate studies
Person responsible
Tuomas Virtanen, Konsta Koppinen
Lessons
| Study type | P1 | P2 | P3 | P4 | Summer | Implementations | Lecture times and places |
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Requirements
Completed project work and a report.
Principles and baselines related to teaching and learning
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Learning outcomes
After completing this course the student will have hands-on experience of the Cambridge Hidden Markov Model Toolkit (HTK) and will be able to independently implement a word-based speech recognition system.
Content
| Content | Core content | Complementary knowledge | Specialist knowledge |
| 1. | Implementation of a digit recognizer using HTK (Hidden Markov Model-toolkit). | ||
| 2. | Calculation of feature vectors, language modelling, estimation of the parameters of an acoustic model using training data, evaluation of a speech recognizer |
Evaluation criteria for the course
Completion of the project work.
Assessment scale:
Evaluation scale passed/failed will be used on the course
Study material
| Type | Name | Author | ISBN | URL | Edition, availability, ... | Examination material | Language |
| Book | "The HTK Book Version 3.3" | S. Young, G. Evermann, M. Gales, T. Hain, D. Kershaw, G. Moore, J. Odell, D. Ollason, D. Povey, V. Valtchev, P. Woodland | http://htk.eng.cam.ac.uk/docs/docs.shtml | English | |||
| Book | HTK Book | English |
Prerequisites
| Course | Mandatory/Advisable | Description |
| SGN-4106 Speech Recognition | Mandatory |
Additional information about prerequisites
The course SGN-4106 Speech Recognition can be taken at the same time as SGN-4507.
Prerequisite relations (Requires logging in to POP)
Correspondence of content
| Course | Corresponds course | Description |
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More precise information per implementation
| Implementation | Description | Methods of instruction | Implementation |