Voice Enabled Intelligent Programming Assistant

Ravindu Wataketiya, Navinda Chandrasiri, Ramesh Kithsiri, Hirush Malwatta, Madhuka Nadeeshani, S. Siriwardana
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Abstract

In modern era where software development is of vital importance, software developers are challenged with conditions like Repetitive Strain Injury (RSI) which hinders their ability to work effectively. Furthermore, people with difficulties with using their hands also find it challenging to program in the traditional manner. As a solution, coding with one’s voice has been experimented with, but current solutions lack interactivity and are harder to use and setup leaving much room for improvement in this domain. In this research work, by using input classifier models with accuracies over 90%, intent classifiers with accuracies over 70%, code parsing and various human computer interaction techniques, we developed a conversationally interactive, programming language agnostic, easy to setup and easy to use Voice Coding Assistant. This will potentially help a global audience of programmers to achieve their goals and improve productivity and lead a healthier life. We have named the system thus developed, “Venic”.
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语音智能编程助手
在软件开发至关重要的现代时代,软件开发人员面临着重复性劳损(RSI)等条件的挑战,这阻碍了他们有效工作的能力。此外,使用双手有困难的人也发现以传统方式编程具有挑战性。作为一种解决方案,人们已经尝试过用声音编码,但目前的解决方案缺乏交互性,而且更难使用和设置,这给这个领域留下了很大的改进空间。在本研究中,我们通过使用准确率超过90%的输入分类器模型、准确率超过70%的意图分类器、代码解析和各种人机交互技术,开发了一个会话交互、编程语言无关、易于设置和易于使用的语音编码助手。这将潜在地帮助全球程序员实现他们的目标,提高生产力,过上更健康的生活。我们把这样开发的系统命名为“Venic”。
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