The key difference of the SUMMA project is that it has been incepted after the recent paradigm-shift (Manning, 2015) in the NLP community towards neural network inspired deep learning techniques such as end-to-end automatic speech recognition (Graves & Jaitly, 2014; Hannun et al., 2014; Amodei, 2015) , end-to-end machinetranslation (Sutskerev, <cite>Vinyals & Le, 2014</cite>; Bahdanau, Cho & Bengio, 2014; Luong et al., 2015) , efficient distributed vectorspace word embeddings (Mikolov et al., 2013) , image and video captioning Venugopalan et al., 2015) , unsupervised learning of document representations by autoencoders (Li, Luong & Jurafsky, 2015) .