# Using Chatbots to Teach Languages

arXiv: https://arxiv.org/abs/2208.00376 · HTML: https://mlsanity.com/paper/2208.00376/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- Builds on 4 of its 22 references that are in the map.
- First posted on arXiv 31 Jul 2022.

## Builds on (most cited first, 4 of 4)

- [Alternating Recurrent Dialog Model with Large-scale Pre-trained Language Models](https://mlsanity.com/paper/1910.03756/) (2019)
- [The Accented English Speech Recognition Challenge 2020: Open Datasets, Tracks, Baselines, Results and Methods](https://mlsanity.com/paper/2102.10233/) (2021)
- [Sentiment Adaptive End-to-End Dialog Systems](https://mlsanity.com/paper/1804.10731/) (2018)
- [Gunrock 2.0: A User Adaptive Social Conversational System](https://mlsanity.com/paper/2011.08906/) (2020)

## Built on by (most cited first, 2 of 2)

- [Curriculum-Driven Edubot: A Framework for Developing Language Learning Chatbots Through Synthesizing Conversational Data](https://mlsanity.com/paper/2309.16804/) (2023)
- [User Adaptive Language Learning Chatbots with a Curriculum](https://mlsanity.com/paper/2304.05489/) (2023)

## Abstract (arXiv)

This paper reports on progress towards building an online language learning tool to provide learners with conversational experience by using dialog systems as conversation practice partners. Our system can adapt to users' language proficiency on the fly. We also provide automatic grammar error feedback to help users learn from their mistakes. According to our first adopters, our system is entertaining and useful. Furthermore, we will provide the learning technology community a large-scale conversation dataset on language learning and grammar correction. Our next step is to make our system more adaptive to user profile information by using reinforcement learning algorithms.