视障人士的数据结构和算法教育聊天机器人

Vidhish Panchal, Lakshmi Kurup
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引用次数: 0

摘要

视障人士发现很难从教育网站上学习,即使他们有很多知识可以提供。由于缺乏独立性,他们对使用在线工具学习没有信心。当学生不得不在不同的网站上搜索自己疑惑的答案时,这几乎成为了每个学生都要面对的一个问题。聊天机器人是一种模拟人类互动的对话式人工智能技术。如果聊天机器人支持语音功能,用户与它互动会更舒适。我们提出的解决方案是一个支持语音和多语言的聊天机器人。它可以与180多种全球语言进行交互,尽管在本文中,我们主要关注印地语。它可以帮助视障人士和正常学生,因为他们可以通过与语音机器人对话来学习。我们的语音机器人可以教学生许多关于数据结构和算法的概念。它从生成的.mp3文件接收到基于语音的响应。对于已经训练了70多个意图的语音机器人系统,我们使用了RASA NLU原理。它已部署到我们的电子学习网络应用程序。聊天机器人与python翻译模块中提到的所有语言兼容。该聊天机器人将从麦克风接收到的语音进行识别并转换为文本,并与训练好的意图信息进行匹配,从而给出最合适的答案,并将文本转换为语音,并在多意图分类的情况下以选择的语言呈现文本和说话。我们制作了一个自定义管道,并应用了各种策略来提高管道的性能。几乎所有的问题都能被语音机器人正确回答,这使得沟通更加有效。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Educational chatbot on Data Structures and Algorithms for the visually impaired
Visually impaired people find it difficult to study from educational websites, even though they have a lot of knowledge to provide. They are unable to feel confident about using online tools to learn because of their lack of independence. This becomes a problem for almost every student when they have to search through different websites for answers to their doubts. A chatbot is a conversational AI technology that simulates human interaction. It is more comfortable for users to interact with a chatbot if it is voice-enabled. Our proposed solution is a chatbot that is voice-enabled as well as multilingual. It can interact with more than 180 global languages, although, in this paper, we have focused on the Hindi language. It can help visually impaired people as well as normal students, as they can learn by just having a conversation with the voice bot. Our voice bot can teach students many concepts regarding data structures and algorithms. It gives the user a speech-based response received from a generated .mp3 file. For the voice-bot system, which has been trained with more than 70 intents, we have utilized the RASA NLU principle. It has been deployed onto our e-learning web application. The chatbot is compatible with all the languages mentioned in the python translate module. This chatbot recognizes and converts the speech received from the microphone into text and matches with the trained intents information, and accordingly gives the most appropriate answer and converts text-to-speech and presents the text and speaks in the language selected along with multi-intent classifications. We have made a custom pipeline and also applied various policies to it to improve pipeline performance. Nearly all of the queries are correctly answered by the voice bot, which makes communication more effective.
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