Title:

Speech Signal Processing

Code:ZRE
Ac.Year:2018/2019
Sem:Summer
Curriculums:
ProgrammeField/
Specialization
YearDuty
IT-MSC-2MBI-Compulsory-Elective - group S
IT-MSC-2MBS-Elective
IT-MSC-2MGM1stCompulsory
IT-MSC-2MIN-Compulsory-Elective - group C
IT-MSC-2MIS-Elective
IT-MSC-2MMM-Elective
IT-MSC-2MPV-Compulsory-Elective - group G
IT-MSC-2MSK2ndCompulsory-Elective - group B
Language of Instruction:Czech
Public info:http://www.fit.vutbr.cz/study/courses/ZRE/public/
Credits:5
Completion:examination (written)
Type of
instruction:
Hour/semLecturesSeminar
Exercises
Laboratory
Exercises
Computer
Exercises
Other
Hours:26201212
 ExamsTestsExercisesLaboratoriesOther
Points:51140629
Guarantor:Černocký Jan, doc. Dr. Ing. (DCGM)
Lecturer:Černocký Jan, doc. Dr. Ing. (DCGM)
Instructor:Mošner Ladislav, Ing. (DCGM)
Žmolíková Kateřina, Ing. (DCGM)
Faculty:Faculty of Information Technology BUT
Department:Department of Computer Graphics and Multimedia FIT BUT
Follow-ups:
Speech Processing Systems (SRE), DCGM
Schedule:
DayLessonWeekRoomStartEndLect.Gr.Groups
Wedexam - 2. oprava2019-06-05E104 09:0010:501MIT 2MIT
Wedexercise2019-04-24E105 11:0012:501MIT 2MIT
Thuexam - řádná2019-05-16E105 15:0017:501MIT 2MIT
Thuexam - 1. oprava2019-05-30E104 15:0016:501MIT 2MIT
 
Learning objectives:
  To provide students with the knowledge of basic characteristics of speech signal in relation to production and hearing of speech by humans. To describe basic algorithms of speech analysis common to many applications. To give an overview of applications (recognition, synthesis, coding) and to inform about practical aspects of speech algorithms implementation.
Description:
  Applications of speech processing, digital processing of speech signals, production and perception of speech, introduction to phonetics, pre-processing and basic parameters of speech, linear-predictive model, cepstrum, fundamental frequency estimation, coding - time domain and vocoders, recognition - DTW and HMM, synthesis. Software and libraries for speech processing.
Learning outcomes and competencies:
  The students will get familiar with basic characteristics of speech signal in relation to production and hearing of speech by humans. They will understand basic algorithms of speech analysis common to many applications. They will be given an overview of applications (recognition, synthesis, coding) and be informed about practical aspects of speech algorithms implementation. The students will be able to design a simple system for speech processing (speech activity detector, recognizer of limited number of isolated words), including its implementation into application programs.
Syllabus of lectures:
 
  1. Introduction, applications of speech processing. 
  2. Digital processing of speech signals.
  3. Speech production and its signal processing model. 
  4. Pre-processing and basic parameters of speech, cepstrum.
  5. Linear-predictive model. 
  6. Fundamental frequency estimation.
  7. Speech coding - basics
  8. CELP Speech coding. 
  9. Speech recognition - basics, DTW. 
  10. Hidden Markov models HMM. 
  11. Large vocabulary continuous speech recognition (LVCSR) systems. 
  12. Speaker and language recognition. Neural networks in speech processing. 
  13. Text to speech synthesis. 
Syllabus of numerical exercises:
 
  1. Parameterization, DTW, HMM.
Syllabus of computer exercises:
 
    Except the last one, Matlab is used in labs.
  1. Introduction. 
  2. Linear prediction and vector quantization. 
  3. Fundamental frequency estimation and speech coding. 
  4. Basics of classification. 
  5. Recognition - Dynamic time Warping (DTW).
  6. Recognition - hidden Markov models (HTK).
Fundamental literature:
 
  • Psutka, J.: Komunikace s počítačem mluvenou řečí. Academia, Praha, 1995, ISBN  80-200-0203-0
  • Gold, B., Morgan, N.: Speech and Audio Signal Processing, John Wiley & Sons, 2000, ISBN 0-471-35154-7
  • Rabiner, L., Juang, B.H.: Fundamentals of Speech Recognition, Signal Processing, Prentice Hall, Engelwood Cliffs, NJ, 1993, ISBN 0-13-015157-2
Study literature:
 
  • Gold, B., Morgan, N.: Speech and Audio Signal Processing, John Wiley & Sons, 2000, ISBN 0-471-35154-7
Progress assessment:
  
  • mid-term test 14 pts
  • project 29 pts
  • presentation of results in computer labs 6 pts
 

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