A Chatbot for Image Recommendation in Mobile Language Learning

Abstract

Mobile language learning applications have already shown great promise and have played a significant role in how language learners learn foreign vocabulary. Many mobile language learning applications such as mobile apps, computer programs, chatbots, and electronic dictionaries are developed to support vocabulary learning. Finding images to represent a word, considering the learning contexts, is challenging. Therefore, this article describes the development of a chatbot to provide foreign language learners with images to represent a word to memorize using Telegram messenger platforms. Using Python, Microsoft Azure services, and the Telegram API, this chatbot has been designed to provide five relevant still images from the image search engine to get the images to represent a word immediately. This minimizes learners' time spent searching images and optimizes the planning for their learning activities. This chatbot, AIVAS-iBOT (Appropriate Image-based Vocabulary Acquisition System-Image BOT), was also deployed in Skype and hence could be accessed from Telegram and Skype.