440-4224/01 – Speech Processing (ZŘS)

Gurantor departmentDepartment of TelecommunicationsCredits4
Subject guarantorIng. Jaromír Továrek, Ph.D.Subject version guarantorIng. Jaromír Továrek, Ph.D.
Study levelundergraduate or graduateRequirementOptional
Year2Semesterwinter
Study languageCzech
Year of introduction2016/2017Year of cancellation
Intended for the facultiesFEIIntended for study typesFollow-up Master
Instruction secured by
LoginNameTuitorTeacher giving lectures
PAR0038 Ing. Pavol Partila, Ph.D.
SKA109 Ing. Jan Skapa, Ph.D.
TOV020 Ing. Jaromír Továrek, Ph.D.
Extent of instruction for forms of study
Form of studyWay of compl.Extent
Full-time Credit and Examination 2+2
Part-time Credit and Examination 2+8

Subject aims expressed by acquired skills and competences

After completing the course, students will be able to solve problems in the field of speech processing. They will learn the basic approaches and methods of speech signal processing, such as feature extraction and processing by neural networks or hidden Markov models. They master to implement a simple system to identify the speaker or the recognition of emotion from speech signal.

Teaching methods

Lectures
Tutorials
Experimental work in labs

Summary

Area of speech processing is one of the important part of information and communication technology. The goal of the course is to understand of basic tasks of speech processing which are SI (Speaker Identification), ASR (Automatic Speech Recognition), TTS (Text to Speech) and SER (Speech Emotion Recognition). Acquired skills can be used for design complex systems where the speech processing is used.

Compulsory literature:

MCLOUGHLIN, Ian. Speech and audio processing: a Matlab-based approach. Cambridge: Cambridge University Press, 2016. ISBN 978-1-107-08546-6.

Recommended literature:

BAILLY, Gérard, Pascal PERRIER a Eric VATIKIOTIS-BATESON, ed. Audiovisual speech processing. Cambridge: Cambridge University Press, 2012. ISBN 978-1-107-00682-9. OGUNFUNMI, Tokunbo, Roberto TOGNERI a Madihally NARASIMHA, ed. Speech and audio processing for coding, enhancement and recognition. New York: Springer, 2015. ISBN 978-1-4939-1455-5.

Way of continuous check of knowledge in the course of semester

Test (0-15) points Project (0-25) points

E-learning

http://lms.vsb.cz/

Other requirements

No additional requirements are placed on the student.

Prerequisities

Subject has no prerequisities.

Co-requisities

Subject has no co-requisities.

Subject syllabus:

Subject syllabus 1. Introduction to subject and speech processing, practical applications and its using. 2. Speech production, basic concepts, speech preprocessing (DC Offset, preemphases, segmentation, windowing). 3. Basic features - energy, zero cross ratio (ZCR), Jitter, Shimmer, autocorrelation, fundamental frequency. 4. Spectrum, spectrogram, spectral analysis of vowels and consonants. 5. Cepstrum, cepstral analysis, Mel frequency cepstral coefficients and other speech parameters. 6. Introduction to classification, SOM, k-NN, GMM, ANN and classifier fusion. 7. Speaker identification (SI) and possible approaches. 8. Speech emotion recognition (SER), stress recognition. 9. Automatic speech recognition (ASR) and possible approaches. 10. Text to speech (TTS), speech corpora and open-source projects. Excercise syllabus 1. Introduction, Safety, Conditions for subject completion. 2. Practical exercises – speech preprocessing – DC offset, preemphases, segmentation, windowing. 3. Practical exercises – Feautures extraction – energy, zero cross ratio, fundamental frequency. 4. Practical exercises – Spectral analysis of speech signal. 5. Practical exercises – Features extraction – MFCC, LPC. 6. Test and assigment of project. 7. Design of speaker recognition system - GMM, ANN. 8. Example of project proposal. 9. Speech synthesis. 10. Presentation of projects.

Conditions for subject completion

Full-time form (validity from: 2017/2018 Winter semester)
Task nameType of taskMax. number of points
(act. for subtasks)
Min. number of pointsMax. počet pokusů
Credit and Examination Credit and Examination 100 (100) 51
        Credit Credit 36  20
        Examination Examination 64  15 3
Mandatory attendence participation: The maximum leave of absence is 20 %.

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Conditions for subject completion and attendance at the exercises within ISP: Completion of all mandatory tasks within individually agreed deadlines.

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Occurrence in study plans

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2019/2020 (N2647) Information and Communication Technology (2601T013) Telecommunication Technology P Czech Ostrava 2 Optional study plan
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Assessment of instruction

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