Sound and Music Computing

Course Structure

1. [\'Core Courses (25 ECTS)\', \'Optional Courses (15 ECTS)\', \'Thesis Project (20 ECTS)\', \'Complementary Courses (extra courses for up to 50 additional ECTS)\', \'Audio Signal Processing for Music Applications: Covers signal processing methodologies and technologies specific for audio and music applications. Special emphasis is given to the use of spectral processing techniques for the description and transformation of sound and music signals.\', \'Music Information Retrieval: This course provides a survey of the field of Music Information Retrieval (MIR), with a special emphasis on techniques for audio content description in terms of different facets (e.g. melody, harmony, rhythm, timbre), temporal scopes and abstraction levels. We also study methods for music context description and current work on user analysis and modeling, addressing the recent trend towards user-centric and adaptive approaches and systems. We also examine how various MIR approaches are evaluated and discuss about the major open challenges in the field.\', \'Music Perception and Cognition: Goes over the principles, structures and functions that make possible humans to perceive and understand sound and music, presented from empirical and computational point of view. The psychophysics of the transduction, the neural encoding of the acoustic input, the perceptual organization of audio streams, musical memory, melodic, rhythmic and tonal cognition, emotion and music, and the development and learning of musical capabilities.\', \'Real-time Interaction: Starts by analyzing the concepts of "interaction", "interactivity" and "real-time" from a general purpose perspective, studying both the human and the technical aspects. Then it concentrates on real-time music applications, giving a special emphasis to the study and the possibilities of mapping techniques. Practical examples are implemented and evaluated using the Pure Data programming language and the sensing capabilities of smartphones and mobile devices.\', \'Research Methods: Reviews of the graduate studies research context, skills and methodologies, introducing the essential aspects in research proposal writing and research reporting.\', \'Advanced Topics in SMC: Seminar covering core methodological and application topics of relevance to Sound and Music Computing.\', \'Audio and Music Processing Lab: State-of-the-art methods and tools for the automatic processing (focusing on its generation and transformation) of music content.\', \'Music Recording and Mixing: Theoretical and practical examination of the most usual microphonic and multitrack recording techniques, the audio processing techniques that are used in a musical recording, and the technical and practical problems that need to be addressed in mixing.\', \'Linear and Nonlinear Time Series Analysis: After introducing the relevant theoretical concepts of dynamic systems, the course presents the underlying theoretical principles of linear time series analysis, nonlinear time series analysis and the concept of surrogates.\', \'Advanced Interface Design: Paradigms, methods and tools used in construction of complex multimodal interfaces between people and artefacts.\', \'Systems Design, Integration and Control: Paradigms within design, integration and control of truly feasible complex systems, with a special stress on neuromorphic principles underlying biological, interactive, cognitive and emotive systems.\', \'Research Seminar: Weekly research seminars with presentations related to the research in Information and Communication Technologies.\', \'Web Intelligence: Study how to gather, process, search and mine data in the Web and its applications to search engines. Understand the basic concepts behind information retrieval and data mining.\', \'Natural Language Interaction: The subject covers central themes related to interaction with intelligent agents through natural language. The approach will be built on models of written dialog, analysis and generation of natural language, and implementations.\', \'Cognitive Science and Psychology: Mind, Brain and Behaviour: The seven central disciplines that form traditional cognitive science, showing how the concepts and paradigms of these disciplines bring complementary visions of mind, brain and behaviour.\', \'Machine Learning: The course covers the theory, definition, and implementation of various machine learning methods and algorithms. These are algorithms that generalize from labeled or unlabelled examples.\', \'Courses from the undergraduate programs in engineering of the Polytechnic School covering topics such as: Audio Signal Processing, Software Engineering, Data Structures, Software Programming, Artificial Intelligence, Music Technology, Mathematics, and Interactive Systems (many undergraduate courses are taught in Spanish or Catalan).\']