Natural Language Translator Correctness Prediction

Abstract

Open Access Research articlecorresponding regions and Baidu with 63% of market share in China. This one of our conducted survey with its results made us think wider into this topic of language translation.Rather than analyzing only Google Translate and focusing only on English, we broaden our scope to other languages. Connecting with our survey respondents also helped us obtain initial data samples for language pairs not only involving English, such as German-to-Russian and Italian-to-French. Some of the survey respondents agreed to expertly verify samples of such translation accuracy, which helped us greatly to launch our mobile RN-Chatter application with a big variety of supported languages.Our main contribution to the topic of intelligent data mining is the innovative idea of applying fairly simple method RN to the complicated topic of translation correction predictions. Through integrating the value of predicted translation correctness in the best way to the chatting application, the messager facilitates the communication among users using various natural languages. Showing our users on receiving part of the conversation the value of the translation correctness makes them being aware of how trustworthy the provided translation is in real time, which helps to improve the ultimate correctness over time by applying our new method RN method.This approach of integrating RN to real-time messager greatly decreases the potential level of overall misunderstanding in international communications. It is a direct path to benefit potentially very large number of users through the friendly interface of RN-chatters. Overall the RN method and its accompanying application, RN-chatter, make it possible to improve international communications, which is now in the mainstream of the Artificial Intelligence and Machines Learning research.As we see in the news channels on the daily basis, many countries and their people in the world stay completely or partially disconnected from others, losing the ability to be understood and to understand others as the distance grows. This RN-chatter has the potential to connect people and end the era of isolations and conflicts caused by misunderstanding. Many existing messagers do provide language translation features. But as we discussed AbstractThis paper presents a new approach to predictive data analytics, called Radius of Neighbors (RN), and its mobile application, a multilingual RN-Chatter, devoted to improving communication among people, speaking different languages. RN is a modeless method of supervised machine learning, what makes it a fairly simple but effective way of analyzing big amounts of data while keeping an acceptable speed of execution and taking up little run-time space. In the first preparatory stage of our research, we discovered that RN gives better results than well-known K-Nearest Neighbors (KNN) in some cases. We then extended our research to simulating the adjustments of floating radiuses, various volumes of the training data sets and ups and downs of the dimensions ...

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