Prototype of a robotic system to assist the learning process of English language with text-generation through DNN
This is an incremental application for English language self-learners, using existing methods on a new domain.
The authors tackled the problem of English language learning by developing a robotic system that uses LSTM neural networks for text generation, resulting in an increment in the Grammatical Range of learners as measured by IELTS rubric.
In the last ongoing years, there has been a significant ascending on the field of Natural Language Processing (NLP) for performing multiple tasks including English Language Teaching (ELT). An effective strategy to favor the learning process uses interactive devices to engage learners in their self-learning process. In this work, we present a working prototype of a humanoid robotic system to assist English language self-learners through text generation using Long Short Term Memory (LSTM) Neural Networks. The learners interact with the system using a Graphic User Interface that generates text according to the English level of the user. The experimentation was conducted using English learners and the results were measured accordingly to International English Language Testing System (IELTS) rubric. Preliminary results show an increment in the Grammatical Range of learners who interacted with the system.