EchoRob: Echo State Networks for Developing Language Robots
Persons participating in the project
Here, we propose to develop the Reservoir Computing (RC) paradigm — in particular Echo State Networks (ESN) with incremental learning — to model language comprehension at the sentence level given sequential inputs of words or phonemes. Based on our initial research, a model processing syntactic sentence structures was able to demonstrate generalisation and online prediction capabilities while processing sequential input.
For less frequent inputs, the model provided potential explanation for human electrophysiological data. Building on this research, a new model is proposed with the following objectives:
On Saturday 7 November 2015, Dr. X. Hinaut and J. Twiefel participated at the 6th Nacht des Wissens (Night of Science) in Hamburg. At their booth, they showed a demo with a Nao humanoid robot talking to visitors. They also showed a video explaining how a robot learns to name objects based on Convolutional Neural Networks, the DOCKS system and the sentence comprehension model central to the EchoRob project. Several motivated Bachelor and Master students helped as well to explain to numerous visitors how the whole system works (in German and English).
Hinaut, X., Twiefel, J., Petit, M., Dominey, P., Wermter, S. A Recurrent Neural Network for Multiple Language Acquisition: Starting with English and French, Conference on Neural Information Processing Systems (NIPS 2015), Workshop on Cognitive Computation: Integrating Neural and Symbolic Approaches, Montreal, Canada, 2015.
Hinaut, X., Twiefel, J., Borghetti Soares, M., Barros, P., Mici, L., Wermter, S. Humanoidly Speaking – How the Nao humanoid robot can learn the name of objects and interact with them through common speech. International Joint Conference on Artificial Intelligence (IJCAI), Video Competition, Buenos Aires, Argentina, 2015.
Hinaut, X., Wermter, S. An Incremental Approach to Language Acquisition: Thematic Role Assignment with Echo State Networks. In Wermter, S., et al., editors. Proceedings of the 24th International Conference on Artificial Neural Networks (ICANN 2014), pp. 33-40, Springer Heidelberg. Hamburg, DE, September 2014.
This research project is supported by a Marie Curie Intra European Fellowship within the 7th European Community Framework Programme: EchoRob project (PIEF-GA-2013-627156).