Course detail

Speech Signal Processing

FIT-ZREAcad. year: 2017/2018

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.

Language of instruction

Czech

Number of ECTS credits

Mode of study

Not applicable.

Guarantor

prof. Dr. Ing. Jan Černocký

Department

Department of Computer Graphics and Multimedia (UPGM)

Learning outcomes of the course unit

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.

Prerequisites

There are no prerequisites

Co-requisites

Not applicable.

Planned learning activities and teaching methods

Not applicable.

Assesment methods and criteria linked to learning outcomes

Study evaluation is based on marks obtained for specified items. Minimimum number of marks to pass is 50.

Course curriculum

Syllabus of lectures:

Introduction, applications of speech processing, sciences relevant for SP, informational content of speech.
Digital processing of speech signals.
Speech production and perception, basic notions from psycho-acoustics, applications in speech processing.
Introduction to phonetics, international norms for phoneme mark-up.
Pre-processing and basic parameters of speech.
Linear-predictive model, spectrum using LP, applications of LP.
Cepstral analysis, Mel-frequency cepstrum.
Determination of fundamental frequency.
Speech coding
Speech recognition - dynamic programming DTW, hidden Markov models HMM
Speech synthesis
Software and libraries for speech processing.

Syllabus of numerical exercises:

Parameterization, DTW, HMM.
Presentation of projects.

Syllabus of computer exercises:

Except the last one, Matlab is used in labs.
Frames, windows, spectrum, pre-processing.
Linear prediction (LPC).
Fundamental frequency estimation.
Coding.
Recognition - Dynamic time Warping (DTW).
Recognition - hidden Markov models (Hidden Markov Model Toolkit - HTK).

Work placements

Not applicable.

Aims

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.

Specification of controlled education, way of implementation and compensation for absences

mid-term test 14 pts
projects 29 pts
presentation of results in computer labs 6 pts

Recommended optional programme components

Not applicable.

Prerequisites and corequisites

Not applicable.

Basic literature

Psutka, J.: Komunikace s počítačem mluvenou řečí. Academia, Praha, 1995, ISBN 80-200-0203-0

VUT

Faculties

University Institutes

Parts

Speech Signal Processing