Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: In previous research a model for thematic role assignment (θRARes) was proposed, using the Reservoir Computing paradigm. This language com- prehension model consisted of a recurrent neural network (RNN) with fixed random connections which models distributed processing in the prefrontal cor- tex, and an output layer which models the striatum. In contrast to this previous batch learning method, in this paper  explored a more biological learning mechanism. A new version of the model (i-θRARes) was developed that per- mitted incremental learning, at each time step. Learning was based on a stochastic gradient descent method.  report here results showing that this incremental version was successfully able to learn a corpus of complex gram- matical constructions, reinforcing the neurocognitive plausibility of the model from a language acquisition perspective.
['Xavier Hinaut', 'Stefan Wermter']
I am writing a research paper on a idea An Incremental Approach to Language Acquisition: Thematic Role Assignment with Echo State Networks
[{"from": "human", "value": "I am writing a research paper on a idea An Incremental Approach to Language Acquisition: Thematic Role Assignment with Echo State Networks"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: In previous research a model for thematic role assignment (\u03b8RARes) was proposed, using the Reservoir Computing paradigm. This language com- prehension model consisted of a recurrent neural network (RNN) with fixed random connections which models distributed processing in the prefrontal cor- tex, and an output layer which models the striatum. In contrast to this previous batch learning method, in this paper  explored a more biological learning mechanism. A new version of the model (i-\u03b8RARes) was developed that per- mitted incremental learning, at each time step. Learning was based on a stochastic gradient descent method.  report here results showing that this incremental version was successfully able to learn a corpus of complex gram- matical constructions, reinforcing the neurocognitive plausibility of the model from a language acquisition perspective."}]