An Natural Language Processed Web Application that Interpret and Convert English to Python Code

Sunny Zhao, Ang Li
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Abstract

As the exchange between natural language and program code gradually becomes the need of industry, more and more interpreters and translators are required. Such natural language interpreters and converters can benefit society in a variety of fields, such as service industry, communication industry, and engineering industry [6]. Concise and accurate language processors will greatly boost the productivity of bottom repetitive works, provide examples and inspirations for students and industry workers, and become the tendency of the future. This paper introduces an application using natural language processing and neural network to effectively interpret and translate English to Python code, and detailly present the structural flow of the application [7]. This paper will also introduce the structure of the neural network, its validity, and how the python torch was applied and integrated. Furthermore, it will demonstrate the application and limitation of this model as well as its future improvements. We applied our application to educational needs and conducted qualitative evaluation of the approach. The result shows a beneficial and potential effect that is applicable to a greater field.
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一个自然语言处理的Web应用程序,解释和转换英语到Python代码
随着自然语言和程序代码之间的交流逐渐成为工业的需要,对口译员和笔译员的需求也越来越大。这样的自然语言解释器和转换器可以在服务行业、通信行业和工程行业等各个领域造福社会。简洁准确的语言处理器将大大提高底层重复性工作的生产率,为学生和行业工作者提供范例和启发,成为未来的趋势。本文介绍了一个利用自然语言处理和神经网络有效地将英文代码翻译成Python代码的应用程序,并详细介绍了应用程序[7]的结构流程。本文还将介绍神经网络的结构、有效性以及python torch的应用和集成。此外,本文还将论证该模型的应用和局限性以及未来的改进。我们将我们的应用程序应用于教育需求,并对该方法进行定性评估。结果表明,该方法具有良好的潜在效果,可应用于更广泛的领域。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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