Creation of algorithms to understand complex real-world signals, including speech, music, images, videos and biological signals. Fundamental knowledge to be able to understand, classify and decompose complex signals. Machine learning techniques, including networks of neurons and signal processing techniques (for example representations STFT, Filterbank, MFCC). Design of systems for applications such as speech recognition, speech enhancement/separation, speech synthesis and sound, classification of sound events, generative models for audio and images, analysis of brain/biological signals, and others. Tangible experience deep learning tools applied to relevant problems of today.
Creation of algorithms to understand complex real-world signals, including speech, music, images, videos and biological signals. Fundamental knowledge to be able to understand, classify and decompose complex signals. Machine learning techniques, including networks of neurons and signal processing techniques (for example representations STFT, Filterbank, MFCC). Design of systems for applications such as speech recognition, speech enhancement/separation, speech synthesis and sound, classification of sound events, generative models for audio and images, analysis of brain/biological signals, and others. Tangible experience deep learning tools applied to relevant problems of today.
