Prototype of a robotic system to assist the learning process of English language with text-generation through DNN

TL;DR

This paper presents a humanoid robotic system prototype that uses LSTM neural networks to generate English text, aiding self-learners by adapting to their language level and improving grammatical skills.

Contribution

The work introduces a novel robotic system with a text-generation module tailored for English learning, integrating NLP with interactive robotics for language education.

Findings

Learners showed increased grammatical range after interaction.

The system's text generation adapts to user English levels.

Preliminary results indicate improved language skills.

Abstract

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.