Project Details

Neural Representations in multi-modal and multi-lingual modeling

Project Period: 1. 1. 2019 - 31. 12. 2023

Project Type: grant

Code: GX19-26934X

Agency: Czech Science Foundation

Program: Grantové projekty exelence v základním výzkumu EXPRO - 2019

Czech title
Neuronové reprezentace v multimodálním a mnohojazyčném modelování

deep learning;machine learning;neural networks;continuous representations;natural language processing;speech and text processing;machine translation;multi-modality;multi-linguality


The NEUREM3 project encompasses basic research in speech processing (SP) and natural language processing (NLP) with accent on multi-linguality and multi-modality (speech and text processing with the support of visual information). Current deep machine learning methods are based on continuous vector representations that are created by the neural networks (NN) themselves during the training. Although empirically, the results of such NNs are often excellent, our knowledge and understanding of such representations is insufficient. NEUREM3 has an ambition to fill this gap and to study neural representations for speech and text units of different scopes (from phonemes and letters to whole spoken and written documents) and representations acquired both for isolated tasks and multi-task setups. NEUREM3 will also improve NN architectures and training techniques, so that they can be trained on incomplete or incoherent data.

Team members
Burget Lukáš, doc. Ing., Ph.D. (UPGM FIT VUT) , research leader
Karafiát Martin, Ing., Ph.D. (UPGM FIT VUT) , team leader
Veselý Karel, Ing., Ph.D. (UPGM FIT VUT) , team leader
Baskar Murali K. (UPGM FIT VUT)
Beneš Karel, Ing. (UPGM FIT VUT)
Han Jiangyu, M.Eng. (UPGM FIT VUT)
Kesiraju Santosh (UPGM FIT VUT)
Peng Junyi, Msc. Eng. (UPGM FIT VUT)
Plchot Oldřich, Ing., Ph.D. (UPGM FIT VUT)
Rohdin Johan A., Dr. (UPGM FIT VUT)
Sarvaš Marek, Bc. (UPGM FIT VUT)








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