HiACC:英语成人和儿童代码交换的语料库
Shruti Singh1, Muskaan Singh2, Virender Kadyan1
1SoCS, University of Petroleum and Energy Studies, Dehradun, Uttarakhand, India.
Data in brief
|August 8, 2025
概括
本研究介绍了HiACC集体,这是一个新的Hinglish语音数据集,用于改进自动语音识别 (ASR) 系统. 该语料库包括成人和儿童演讲者,解决了代码交换通信资源的关键缺口.
科学领域:
- 计算语言学 计算语言学
- 语音处理 语音处理
- 社会语言学 社会语言学
背景情况:
- 代码交换,语言间的交替,在双语者中很常见,特别是在印度与英语 (印度语-英语) 之间.
- 现有的自动语音识别 (ASR) 系统由于缺乏多样化,代表性的数据集,与代码交换数据作斗争,导致更高的文字错误率 (WER).
- 当前的ASR模型显示,与单语言语言相比,在处理代码交换语音时,WER增加了30-50%.
研究的目的:
- 介绍HiACC集体,一个基准的英语语音数据集,旨在提高资源有限的环境中的ASR性能.
- 解决公开可用的代码交换语音数据集的稀缺问题,特别是包括儿童语音的语音数据集.
- 为代码交换的语言和计算分析提供一个有价值的资源.
主要方法:
- 开发HiACC语料库,包括来自成人的3318个音频段和来自儿童的1858个音频段.
- 包括5.24小时的阅读和自发的英语演讲,附有详细的注释和代码切换标签.
- 公开发布的语料库与细分的音频和对齐的成绩单为开放的研究.
主要成果:
- 基线ASR实验表明,在单语言数据上训练的模型的表现明显低,Hinglish测试组的WER约为42%.
- HiACC语料库提供了第一个公开可用的资源,用于代码切换的Hinglish语音,包括成人和儿童发言人.
- 预计数据集的可用性将催化对代码交换语言开发更强大的ASR系统的进展.
结论:
- HiACC 语料库是推动 Hinglish 等代码交换语言的自动语音识别研究的关键资源.
- 这些发现突出了ASR系统面临的代码交换输入和需要专门数据集的挑战.
- 这项工作为多种语言社区提供更具包容性和准确的语音识别技术铺平了道路.
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