针对印度语种的发音纠错系统，支持个性化反馈。
Dhvani: A Weakly-supervised Phonemic Error Detection and Personalized Feedback System for Hindi
- 基于音素分析，结合梵文字母输入实现发音检测。
- 生成合成错读语音用于训练与反馈优化。
- 适合语言学习者及教育技术研究者使用。
计算机辅助发音训练（CAPT）在英语中已得到广泛研究，但在以15亿人为基础的印度语言中仍存在显著空白。尽管每年有数百万人学习这些语言，但针对印度语言的发音工具却极为稀缺。作为全球第四大语言、拥有超过6亿使用者的印地语，其发音改进是填补这一空白的关键第一步。本文提出：1）面向印地语的新型CAPT系统Dhvani；2）生成印地语错读语音的合成方法；3）为学习者提供个性化反馈的新范式。该系统虽常以天城文字符与学习者交互，但核心分析聚焦音素差异，利用印地语高度音素化的拼写系统，对错误发音进行精准分析并提供针对性反馈。
原文摘要 · Abstract (English)
Computer-Assisted Pronunciation Training (CAPT) has been extensively studied for English. However, there remains a critical gap in its application to Indian languages with a base of 1.5 billion speakers. Pronunciation tools tailored to Indian languages are strikingly lacking despite the fact that millions learn them every year. With over 600 million speakers and being the fourth most-spoken language worldwide, improving Hindi pronunciation is a vital first step toward addressing this gap. This paper proposes 1) Dhvani -- a novel CAPT system for Hindi, 2) synthetic speech generation for Hindi mispronunciations, and 3) a novel methodology for providing personalized feedback to learners. While the system often interacts with learners using Devanagari graphemes, its core analysis targets phonemic distinctions, leveraging Hindi's highly phonetic orthography to analyze mispronounced speech and provide targeted feedback.
Thank you to arXiv for use of its open access interoperability. PaperDance 不是 arXiv 官方产品；中文卡片由大模型生成，请以原文为准。