About the Project
The project is going to investigate and develop novel automatic music generation techniques with exploring and applying the state-of-the-art generative models such as generative adversarial networks (GAN) and variational auto-encoder (VAE) as well as deep sequence modelling techniques such as memory augmented recurrent neural networks. In this project, main issues to be studied include effective representation of music notes suitable for music content generation, modelling various music structures that effectively express the notions of harmony and melody, specific music style modelling and transfer and effective yet efficient music generation strategies to be used in deep learning and generative models. In particular, this project is suitable for one who is enthusiastic about music and interested in applying the state-of-the-art machine learning techniques in tackling complex real-world problems.
It is worth highlighting that this is an extremely challenging project of a great novelty. In order to take this project, research experience related to the application of related deep learning techniques may be required. It is also essential to be self-motivated and to have decent background knowledge in music theory, mathematics, machine learning as well as good programming skills. Apart from those stated above, it would be ideal that one has knowledge and skills in performing music, e.g., vocal or playing a musical instrument.
If you are interested in this project, please first visit my research student page: http://staff.cs.manchester.ac.uk/~kechen/ for the required materials and information prior to contacting me.
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