用语音支持多语言编程学习，让非英语学生也能轻松学编程。
CodeVaani: A Multilingual, Voice-Based Code Learning Assistant
- 通过语音输入+本地化ASR+代码理解模型，实现多语言交互
- 28名初学者测试中回答准确率达75%，超80%用户评价积极
- 适合英语能力弱的编程初学者，尤其惠及印度等多语地区
编程教育通常以英语为基础、依赖文本交互，对印度等多语地区的学生构成障碍。我们提出CodeVaani，一个集成于IIT Bombay开发的学习管理系统Bodhitree的多语言语音驱动编程助教。该系统结合印地语等语言的语音识别（Indic ASR）、面向代码的转录优化模块及代码理解模型，支持以母语语音提问并返回文字与语音双模响应。在28名初学者的测试中，系统实现75%的回答准确率，超过80%参与者给予正面评价。相比传统课堂辅导，该框架具备按需可用、可扩展性强、多语言支持等优势，有效降低英语水平不足学生的入门门槛。演示视频与补充材料已公开。
原文摘要 · Abstract (English)
Programming education often assumes English proficiency and text-based interaction, creating barriers for students from multilingual regions such as India. We present CodeVaani, a multilingual speech-driven assistant for understanding code, built into Bodhitree [1], a Learning Management System developed at IIT Bombay. It is a voice-enabled assistant that helps learners explore programming concepts in their native languages. The system integrates Indic ASR, a codeaware transcription refinement module, and a code model for generating relevant answers. Responses are provided in both text and audio for natural interaction. In a study with 28 beginner programmers, CodeVaani achieved 75% response accuracy, with over 80% of participants rating the experience positively. Compared to classroom assistance, our framework offers ondemand availability, scalability to support many learners, and multilingual support that lowers the entry barrier for students with limited English proficiency. The demo will illustrate these capabilities and highlight how voice-based AI systems can make programming education more inclusive. Supplementary artifacts and demo video are also made available.
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