论文标题
卢甘达文字对语音机器
Luganda Text-to-Speech Machine
论文作者
论文摘要
在乌干达，卢甘达是说话最多的母语。它用于非正式和正式业务交易中的沟通。与TTS相关的全球技术初创公司的开发主要是用英语，法语等语言。这些语言由Google，Microsoft等人添加到TTS引擎中，允许这些地区的开发人员创新TTS产品。不支持卢甘达（Luganda），因为该语言没有在这些引擎上构建和培训。在这项研究中，我们分析了Luganda的语言结构和结构，然后提出并开发了Luganda TTS。该系统是使用本地采购的Luganda语言文本和音频构建和培训的。该引擎现在能够捕获文本并大声朗读。我们使用MRT和MOS测试了准确性。 MRT和MOS测试结果非常好，MRT具有更好的结果。结果总分为71％。这项研究将增强乌干达NLP差距的先前解决方案，并提供原始数据，以便可以在该领域进行其他研究。
In Uganda, Luganda is the most spoken native language. It is used for communication in informal as well as formal business transactions. The development of technology startups globally related to TTS has mainly been with languages like English, French, etc. These are added in TTS engines by Google, Microsoft among others, allowing developers in these regions to innovate TTS products. Luganda is not supported because the language is not built and trained on these engines. In this study, we analyzed the Luganda language structure and constructions and then proposed and developed a Luganda TTS. The system was built and trained using locally sourced Luganda language text and audio. The engine is now able to capture text and reads it aloud. We tested the accuracy using MRT and MOS. MRT and MOS tests results are quite good with MRT having better results. The results general score was 71%. This study will enhance previous solutions to NLP gaps in Uganda, as well as provide raw data such that other research in this area can take place.
