用于识别库尔德语声音方言的数据集
Karwan M Hama Rawf1, Sarkhel H Taher Karim1, Ayub O Abdulrahman1
1Department of Computer Science, College of Science, University of Halabja, Halabja, Kurdistan Region, Iraq.
Data in brief
|March 4, 2024
概括
这项研究引入了用于库尔德语方言识别 (DRS) 的新数据集. 这种资源对于通过计算库尔德语语言的语言变异来改进语音识别系统至关重要.
科学领域:
- 语音分析 语言分析
- 计算语言学 计算语言学
- 语音学 语音学 语音学
背景情况:
- 语音识别系统受到扬声器变化的负面影响,包括年龄,性别和方言.
- 方言识别系统 (DRS) 可以集成到语音识别中,以减轻由方言差异引起的性能问题.
- 库尔德语及其独特的方言缺乏用于自动方言识别的专用数据集.
研究的目的:
- 解决库尔德语方言识别资源的稀缺问题.
- 引入和评估用于库尔德语自动方言识别的新型数据集.
- 促进库尔德语语言改进的语音识别模型的开发.
主要方法:
- 使用哈拉布贾大学计算机科学系收集的实验数据编制了一个数据集.
- 该数据集包括来自三个主要库尔德语方言的样本:北库尔德语 (巴迪尼语),中库尔德语 (索拉尼语) 和哈瓦拉米语.
- 评估了数据集适用于开发自动方言识别系统的适用性.
主要成果:
- 一个新的库尔德语方言识别数据集已经创建和评估.
- 数据集包括库尔德语的三个主要方言,为研究提供了基础.
- 这一数据集的可用性是朝着加强库尔德语语音识别技术迈出的重要一步.
结论:
- 开发的数据集对于推进库尔德语语言的自动方言识别至关重要.
- 这种资源将使创建更准确和更强大的语音识别系统适合库尔德语说话者.
- 库尔德语语音处理的进一步研究和开发现在可以通过这个基础数据集来进行.
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