Biblio

Export 8 results:
Sort by: Author [ Title (Desc)] Type Year
Filters: Author is Miron, M.  [Clear All Filters]
A B C D E F G H I J K L M N O P Q R S T U V W X Y Z 
S
Miron, M. (2018).  Source Separation Methods for Orchestral Music: Timbre-Informed and Score-Informed Strategies. Department of Information and Communication Technologies. 299. Abstract
O
Serrà, J., Suris D., Miron M., & Karatzoglou A. (2018).  Overcoming catastrophic forgetting with hard attention to the task. The 35th International Conference on Machine Learning (ICML 2018) . Abstract
M
Chandna, P., Miron M., Janer J., & Gómez E. (2017).  Monoaural Audio Source Separation Using Deep Convolutional Neural Networks. 13th International Conference on Latent Variable Analysis and Signal Separation (LVA ICA2017).
application/pdf iconmonoaural-audio-source.pdf
Miron, M., Janer J., & Gómez E. (2017).  Monaural score-informed source separation for classical music using convolutional neural networks. 18th International Society for Music Information Retrieval Conference.
I
Janer, J., Gómez E., Martorell A., Miron M., & de Wit B. (2016).  Immersive Orchestras: audio processing for orchestral music VR content. VSGAMES 2016 - 8th International Conference on Virtual Worlds and Games for Serious Applications. Abstract
G
Miron, M., Janer J., & Gómez E. (2017).  Generating data to train convolutional neural networks for classical music source separation. Proceedings of the 14th Sound and Music Computing Conference. 227-233.
D
Martel, H., & Miron M. (2017).  Data augmentation for deep learning source separation of HipHop songs. 10th International Workshop on Machine Learning and Music. Abstract
C
Miron, M., & Slizovskaia O. (2017).  Convolutional neural networks for audio processing: starting pack. Pydata Barcelona.
intranet