4 papers
Interpretable Timbre Synthesis using Variational Autoencoders Regularized on Timbre Descriptors
Anastasia Natsiou, Luca Longo, Sean O'Leary
Controllable timbre synthesis has been a subject of research for several decades, and deep neural networks have been the most successful in this area. Deep generative models such a…
An investigation of the reconstruction capacity of stacked convolutional autoencoders for log-mel-spectrograms
Anastasia Natsiou, Luca Longo, Sean O'Leary
In audio processing applications, the generation of expressive sounds based on high-level representations demonstrates a high demand. These representations can be used to manipulat…
Audio representations for deep learning in sound synthesis: A review
Anastasia Natsiou, Sean O'Leary
The rise of deep learning algorithms has led many researchers to withdraw from using classic signal processing methods for sound generation. Deep learning models have achieved expr…
A sinusoidal signal reconstruction method for the inversion of the mel-spectrogram
Anastasia Natsiou, Sean O'Leary
The synthesis of sound via deep learning methods has recently received much attention. Some problems for deep learning approaches to sound synthesis relate to the amount of data ne…