Mathematical basis of signal processing General knowledge on potential speech, audio, image, and video processing applications Basic subsystems of speech, audio, image, and video processing applications Use of speech, audio, image, and video processing software Mastering of basic speech, audio, image, and video processing tools Solving speech, audio, image, and video processing problems by using several basic tools Individual- and team-work Analysis and problem-solving capabilities

The goal of this subject is to provide the student with an introduction to speech, audio, image, and video processing. The emphasis is put on lab exercises, so that the student can be assessed according to her work on a final project. The course will finish with an introduction to Convolutional Neural Networks (CNNs), which represent the state-of-the are in many applications. 1.- Introduction 2.- Fundamentals of Multimedia Digitalization - Digital representation of signal and images - Digital compression fundamentals 3.- Introduction to speech and audio technologies - Speech and audio. Production and perception - An outlook of Speech and Audio Applications 4.- Basic Speech and Audio Processing Techniques - Short-term time and frequency analysis 5.- Speech coding - Fundamentals and specifications - Coding strategies - Standards (for digital mobile telephony and voice over IP) 6. Audio Coding - Psychoacoustic principles and perceptual coding - Transform-domain coding - Standards (MP3 and beyond) 7.- Shazam (audio): identificación de contenidos musicales 8. Introduction to image and video processing - Digital images - Color spaces - Pseudocolor and PCA 9. Basic image and video processing techniques - Point operations - Filters - Transforms 10. Edge Detection 11. Image Segmentation 12. Mathematical Morphology 13. Detectors and Descriptors 14. Introduction to CNNs and its applications in Computer Vision

Two teaching activities are proposed: theoretical classes with examples and lab exercises. THEORETICAL CLASSES WITH EXAMPLES (3 ECTS) The theoretical class will be given in the blackboard, with slides or by any other means to illustrate the concepts of the lectures. In these classes the explanation will be completed with examples. In these sessions the student will acquire the basic concepts of the course. It is important to highlight that these classes require the initiative and the personal and group involvement of the students (there will be concepts that the students should develop by themselves). LABORATORY EXERCISES (3 ECTS) Some basic selected concepts learnt during the course are applied in the lab. The students should participate actively in the exercise implementation. There will be two types of lab exercises: - Guided lab exercises: getting used to image processing with MATLAB - Project: image processing problem to be solved in groups.