应用序列到序列语音转换评估二语语音可懂度的初步研究：基于母语者跟读
A Pilot Study of Applying Sequence-to-Sequence Voice Conversion to Evaluate the Intelligibility of L2 Speech Using a Native Speaker's Shadowings
AI总结：
本文通过序列到序列语音转换技术构建虚拟跟读系统，模拟母语者对二语语音的跟读行为，以细粒度反馈帮助二语学习者检测和诊断发音及韵律问题，实验验证了该方法的可行性。
摘要：
二语说话人的话语可能因发音错误和不恰当的韵律而难以理解。在计算机辅助语言学习系统中，通常使用语音识别引擎提供文本反馈。然而，对二语说话人而言，理想的反馈形式应当足够细粒度，使其能够检测和诊断二语说话人话语中难以理解的部分。受语言教师通过语音到语音过程纠正学生发音的启发，这项初步研究利用了一个独特的半平行数据集，该数据集由非母语者（L2）的朗读、对母语者（L1）的跟读及其脚本跟读话语组成。我们探索了利用语音转换技术复现母语者跟读二语语音过程的技术可能性，以创建一个虚拟跟读系统。实验结果表明，该语音转换系统在模拟母语者跟读行为方面具有可行性。虚拟跟读系统的输出在语言和声学两方面都与真实的母语跟读话语表现出合理的相似性。
英文摘要：
Utterances by L2 speakers can be unintelligible due to mispronunciation and improper prosody. In computer-aided language learning systems, textual feedback is often provided using a speech recognition engine. However, an ideal form of feedback for L2 speakers should be so fine-grained that it enables them to detect and diagnose unintelligible parts of L2 speakers' utterances. Inspired by language teachers who correct students' pronunciation through a voice-to-voice process, this pilot study utilizes a unique semi-parallel dataset composed of non-native speakers' (L2) reading aloud, shadowing of native speakers (L1) and their script-shadowing utterances. We explore the technical possibility of replicating the process of an L1 speaker's shadowing L2 speech using Voice Conversion techniques, to create a virtual shadower system. Experimental results demonstrate the feasibility of the VC system in simulating L1's shadowing behavior. The output of the virtual shadower system shows a reasonable similarity to the real L1 shadowing utterances in both linguistic and acoustic aspects.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
