Master of Science in Acoustics, Audio and Vibrations

Train to analyze, design, and apply innovative solutions in acoustic engineering, addressing noise control, vibration management, and audio signal processing with emerging technologies.

Nid: 28800
Syllabus
 

Physical acoustics and structural vibration dynamics (5 ECTS)

You will cover the fundamentals of physical acoustics, structural dynamics, and modal analysis, with applications to vibroacoustic and aeroacoustic systems. Practical examples illustrate sound radiation, flow noise, and the use of structural modes to predict acoustic responses.

Psychoacoustics and sound quality (5 ECTS)

You will examine physiological and perceptual foundations of hearing and their application to sound quality evaluation. Explore key psychoacoustic phenomena, masking, loudness, pitch, timbre, and spatial hearing, alongside perceptual attributes relevant to diverse contexts, including room acoustics, soundscapes, speech, and product design.

Advanced topics in acoustics, audio, and vibrations (5 ECTS)

This part provides an overview of a wide range of current topics in acoustics, audio, and vibrations, including holography, acoustic black holes, metamaterials, 3D audio and auralization, AI applications in voice technology, immersive audio, and sound quality in engineering and heritage contexts.

Experimental techniques for room acoustics and environmental noise (5 ECTS)

Provides practical training in experimental techniques for room acoustics and environmental noise assessment. Conducted in the Acoustics Laboratory, it offers hands-on experience with acoustic instrumentation and measurement methods for evaluating sound insulation, absorption, room acoustics, noise sources, and sound power.

Sound recording and immersive audio (5 ECTS)

Learn the technical principles of sound acquisition, processing, and spatial reproduction through two main areas: sound recording and immersive audio. You will develop engineering skills in transducer selection, microphone array design, signal processing, and spatialization to create high-quality recordings for research, fieldwork, and immersive applications.

Advanced experimental techniques in acoustics, audio, and vibroacoustics (5 ECTS)

Focuses on advanced experimental methodologies in acoustics, audio, and vibroacoustics. Through a series of laboratory exercises, students apply techniques such as experimental modal analysis, near-field acoustic holography, and soundscape evaluation to investigate and characterize acoustic and vibroacoustic phenomena.

Numerical methods for low frequencies: FEM and BEM (5 ECTS)

This part covers finite and boundary element methods for low-frequency acoustics and vibrations, including vibroacoustic coupling and sound radiation in structures and cavities. Practical aspects such as mesh design, stability, and accuracy are also introduced.

Numerical methods for high frequencies: SEA, hybrid methods and ray acoustics (5 ECTS)

You will be introduced to the Statistical Energy Analysis (SEA) for high-frequency vibroacoustics, the hybrid FE-SEA method and related approaches for mid-frequency problems, as well as ray acoustics. Topics include modal energy distribution, subsystem coupling, transmission paths, long-range sound propagation, and practical numerical simulations.

Fundamentals of audio signal processing (5 ECTS)

You will explore how audio signals are represented, manipulated, and analysed in the discrete-time domain, with key techniques including the DFT/FFT, STFT, Z-transform, and FIR/IIR filter design. Through guided exercises and hands-on computational work, students gain both insight and technical proficiency in implementing real-world audio processing algorithms.

Applications and AI in audio signal processing (5 ECTS)

You will explore the use of artificial intelligence techniques in modern audio signal processing. Topics include classical audio features, supervised machine learning, and deep learning architectures such as CNNs, RNNs, and Transformers. You will learn to apply pretrained audio models, autoencoders for anomaly detection, and generative models (GANs, VAEs, diffusion).

Master’s Thesis (10 ECTS)