Speech and Image Technology

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.

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.

Lectures

Interactive teaching

Practical assignements