Speech and Image Technology

Higher education teachers: Dobrišek Simon

Higher education teachers: , Štruc Vitomir
Credits: 6
Semester: summer, summer
Subject code: 64154M

Subject description


  • registration to the 2nd or 3rd year study

Content (Syllabus outline):

  • Introduction: description of the field, short outline of the historical develoment of speech and image technologies.
  • Basic characteristics of visual and auditory perception and human speech-based communication. Representation of speech and image patterns.
  • Pattern recognition: structural description, pattern recognition systems in general, feature extraction, learning, classification and clustering in pattern recognition systems.
  • Speech processing: acquisition and preprocessing, speech features, speech signal segmentation, databases of speech.
  • Speech recognition: types of speech-recognition systems, statistical modelling, acoustic and langauge modelling, semantic analysis of speech.
  • Artificial speech: systems for speech synthesis in general, grapheme-to-phoneme conversion, prosody modelling, speech-synthesis procedures.
  • Dialogue: automated dialogue systems in general, approached to designing human-computer dialogue systems, assessment of dialogue systems.
  • Image technologies: terminology, use-cases, basic image transformations, color images and color spaces, image coding.
  • Image processing: image processing in the spatial and frequency domains, noise models and image restoration, morphological operations and algorithms, edge detection.
  • Advanced algorithms, local descriptors and their applications, object detection in images, object recognition from image data, subspaces for data representation.
  • Image segmentation: clustering techniques and thier application to image segmentation, mean-shift .

Objectives and competences:

The aim of this course is to acquaint students with the field of speech and image technologies and introduce various algoritms, techniques, and methods to acomplish tasks related to this field.

Intended learning outcomes:

After successful completion of the course, students should be able to:

  • define the main approaches to the representation, description, synthesis and recognition of speech and image signals,
  • describe the characteristics, components, structure and capabilities of speech and image-based technologies,
  • use selected programing solutions (APIs) for the development of spoken man – machine communication systems, image processing and image recognition applications,
  • distinguish between different tasks of speech and image technologies and representation and processing methods needed to achieve these tasks,
  • combine basic procedures for representation and processing of speech and image data into complex systems for recognition and synthesis of images and speech,
  • evaluate the accuracy and reliability of speech and image technologies systems.

Learning and teaching methods:

  • lectures,
  • interactive teaching,
  • practical assignements.

Study materials

  1. Mihelič F., Žibert J., Hajdinjak M., Štruc V., Skripta za predmet Govorne in slikovne tehnologije, 1. Izdaja, Ljubljana, Fakulteta za elektrotehniko, 2012
  2. Mihelič F., Signali, Založba FE in FRI, Ljubljana, 2006
  3. Pavešić N., Razpoznavanje vzorcev: uvod v analizo in razumevanje vidnih in slušnih vzorcev, 3. Popravljena in dopolnjena izdaja, Založba FE in FRI, Ljubljana, 2012
  4. Rabiner L., Schafer R., Theory and Applications of Digital Speech Processing, Prentince Hall, 1. Ed., 2010
  5. Gonzales R. C., Woods, R.E., Digital Image Processing, 3 izdaja, Prentice Hall, 2007
  6. R.C. Gonzales, R.E. Woods, S.L. Eddins, Digital image processing using Matlab, 2 izdaja. Gatesmark Publishing, 2009

Study in which the course is carried out

  • 2 year - 1st cycle - Multimedia
  • 3 year - 1st cycle - Multimedia