论文标题
对文本预测和娱乐系统的全面审查和评估
A comprehensive review and evaluation on text predictive and entertainment systems
论文作者
论文摘要
体验沟通和与系统互动的最重要方法之一是处理键入字母或单词后最有可能发生的单词的预测。由于禁用可能以有限的慢速输入文本或输入文本的人,这对残疾人有帮助。同样,这对诵读困难的人和那些对单词咒语不好的人有益。但是,例如,输入技术的下一个单词建议促进了智能手机中的打字过程。这意味着,当用户键入单词时,系统会建议选择用户必要单词的下一个单词。此外,例如,它可以在娱乐中用作GAM,以确定目标单词并在10次预测尝试中达到或解决它。通常,系统依赖于文本语料库,该文本语料库是在系统中提供预测的。因此,编写每个单词都是耗时的,因此,通过减少最可能的单词供用户选择来选择系统中的文本,从而减少时间消耗至关重要,这可以通过下一个单词预测系统来完成。文献中可以找到几种技术,该技术可通过使用不同的方法来进行多种下一个单词的预测系统。在本文中,将讨论针对下一个单词预测系统的其他技术的调查。此外,将讨论对预测系统的评估。然后,将确定一种模态技术从实现的易用性和获得良好结果的角度来确定下一个单词预测系统。
One of the most important ways to experience communication and interact with the systems is by handling the prediction of the most likely words to happen after typing letters or words. It is helpful for people with disabilities due to disabling people who could type or enter texts at a limited slow speed. Also, it is beneficial for people with dyslexia and those people who are not well with spells of words. Though, an input technology, for instance, the next word suggestion facilitates the typing process in smartphones as an example. This means that when a user types a word, then the system suggests the next words to be chosen in which the necessary word by the user. Besides, it can be used in entertainment as a gam, for example, to determine a target word and reach it or tackle it within 10 attempts of prediction. Generally, the systems depend on a text corpus, which was provided in the system to conduct the prediction. Writing every single word is time-consuming, therefore, it is vitally important to decrease time consumption by reducing efforts to input texts in the systems by offering most probable words for the user to select, this could be done via next word prediction systems. There are several techniques can be found in literature, which is utilized to conduct a variety of next word prediction systems by using different approaches. In this paper, a survey of miscellaneous techniques towards the next word prediction systems will be addressed. Besides, the evaluation of the prediction systems will be discussed. Then, a modal technique will be determined to be utilized for the next word prediction system from the perspective of easiness of implementation and obtaining a good result.