Intelligent Data Mining based Method for Efficient English Teaching and Cultural Analysis

The emergence of online education helps improving the traditional English teaching quality greatly. However, it only moves the teaching process from offline to online, which does not really change the essence of traditional English teaching. In this work, we mainly study an intelligent English teaching method to further improve the quality of English teaching. Specifically, the random forest is firstly used to analyze and excavate the grammatical and syntactic features of the English text. Then, the decision tree based method is proposed to make a prediction about the English text in terms of its grammar or syntax issues. The evaluation results indicate that the proposed method can effectively improve the accuracy of English grammar or syntax recognition.

Design of Legal Chinese English Simultaneous Interpretation System based on PSO Algorithm

Aiming at the phenomenon of “wrong words” and “missing words” in the process of Chinese English legal interpretation, a Chinese English legal simultaneous interpretation system based on PSO algorithm is designed. According to the construction requirements of fuzzy neural network, the optimization results of PSO inertia weight are determined, and then the system model optimization based on PSO algorithm is realized with the help of membership function. On this basis, this paper analyzes the key trigger factors of simultaneous interpretation, and distinguishes the specific differences between consecutive interpretation load and simultaneous interpretation by defining the way of legal Chinese English text transmission effect, so as to realize the smooth application of legal Chinese English simultaneous interpretation system based on PSO algorithm. The results shows that, compared with the consecutive interpretation system, the simultaneous interpretation system can effectively solve all the problems of “wrong words” and “missing words” in the process of legal Chinese English document translation, and effectively guarantee the authenticity of document samples.

Impacts Of Extensive Reading on English Vocabulary Learning: A Meta-Analysis

There are many differences in sentence structure between English and Indonesian. In this study, the researchers conducted a comparative analysis of past sentence patterns in English and Indonesian. The purpose of this research is to find out the past sentence patterns of English and Indonesian, and the similarities and differences between them. The methods used to conduct research are qualitative research and descriptive research to compare patterns between English and Indonesian past sentence patterns. A high school textbook named "Interlanguage" is used as English data, which Indonesian students generally use and understand, rather than college students' books, while Indonesian data is a translation of the selected English text for each past sentence pattern. This research shows that there are more differences than similarities between the two languages. There are six differences, Namely: 1) Verb form; 2) Irregular verb be; 3) English generally has four past tenses, but Indonesian does not; 4) progress; 5) perfect progress; 6) English has 7 basics In the past, there are 2 sentence patterns in Indonesian. Researchers found some similarities, namely: 1) perfect aspect; 2) sentence pattern arrangement. Since English and Indonesian have more differences in past tense sentence patterns than similarities, it is expected that Indonesian learners will encounter some difficulties in learning English past. Keywords: comparative analysis, past sentences, sentence patterns, English, Indonesian

THE EFFECT OF USING COMPOSITE PICTURES ON READING COMPREHENSION ACHIEVEMENT

Reading Comprehension is the ability to read text, process it and understand the meaning. It relies on two, interconnected abilities: Word reading be able to decode the symbols on the page and language comprehension being able to understand the meaning of words and sentences . In fact, students generally feel bored and unmotivated in learning English especially in reading skill because English is different from Indonesian so that the students have difficulty in understanding reading English text. They do not know the meaning of some words in the text. Therefore, the teacher’s role becomes important in the teaching and learning process especially in teaching reading. Therefore, appropriate media should be chosen to motivate their students not only to read the text but also comprehend what they read. One of the media that can be used and applied by the teacher is Composite Pictures. A Composite Picture is a large single picture which shows a scene in which a number of people can be seen doing several things. Thus, to know whether or not there was a significant effect of using Composite Pictures on reading comprehension achievement; Composite Pictures was used as media in teaching reading in this research.

A System for Machine Translation from English to Ebira using the Rule-based Approach

This research work is aimed at bridging the knowledge gap between the most popular knowledge rich English language and the minority Ebira language spoken by the Ebira people, a minority ethnic group in part of Nigeria. Across the globe and on the internet, English language has become the most widely used language for knowledge dissemination. And presently, the majority of the indigenous people of Ebiral and also known as “Anebira” are still not proficient in their use of English language which as a result prevents them from gaining full knowledge disseminated in English language. Hence, the need to develop an automated Machine Translation System capable of translating English text to Ebira text which will help the people to tap from the abundant knowledge conveyed in English language for effective and fast development in their social, political, scientific, philosophical and economic areas of life. The system was designed to consolidate on human translators’ effort and not to replace them. A comprehensive study and analysis of the two languages was carried out with the help of Ebira native speakers in Ebiraland Kogi central and some professional English language tutors at FCE Okene. The knowledge gathered provided the basis for the design and testing of the rule base, inference engine, bilingual dictionary which are important components for the proposed automated system for translation of English text to Ebira text using PHP. Making use of the word in the bilingual dictionary, the system will successfully translate your English text to Ebira. The system was evaluated using one of the popular automatic method of evaluating MT systems BLEU (Bilingual Evaluation Understudy). And an accuracy of 81.5% in translation was achieved. An improved system in the future is recommended to accommodate more complex sentences for the more benefit of the good people of Enebira.

Research on Methods of English Text Detection and Recognition Based on Neural Network Detection Model

With the rapid development of computer science, a large number of images and an explosive amount of information make it difficult to filter and effectively extract information. This article focuses on the inability of effective detection and recognition of English text content to conduct research, which is useful for improving the application of intelligent analysis significance. This paper studies how to improve the neural network model to improve the efficiency of image text detection and recognition under complex background. The main research work is as follows: (1) An improved CTPN multidirectional text detection algorithm is proposed, and the algorithm is applied to the multidirectional text detection and recognition system. It uses the multiangle rotation of the image to be detected, then fuses the candidate text boxes detected by the CTPN network, and uses the fusion strategy to find the best area of the text. This algorithm solves the problem that the CTPN network can only detect the text in the approximate horizontal direction. (2) An improved CRNN text recognition algorithm is proposed. The algorithm is based on CRNN and combines traditional text features and depth features at the same time, making it possible to recognize occluded text. The algorithm was tested on the IC13 and SVT data sets. Compared with the CRNN algorithm, the recognition accuracy has been improved, and the detection and recognition accuracy has increased by 0.065. This paper verifies the effectiveness of the improved algorithm model on multiple data sets, which can effectively detect various English texts, and greatly improves the detection and recognition performance of the original algorithm.

Speech to Indian Sign Language Translator

Indian Sign Language is one of the most important and widely used forms of communication for people with speaking and hearing impairments. Many people or communities have attempted to create systems that read the sign language symbols and convert the same to text, but text or audio to sign language is still infrequent. This project mainly focuses on developing a translating system consisting of many modules that take English audio and convert the input to English text, which is further parsed to structure grammar representation on which grammar rules of Indian Sign Language are applied. Stop words are removed from the reordered sentence. Since the Indian Sign Language does not support conjugation in words, stemming and lemmatization will transform the provided word into its root or original word. Then all the individual words are checked in a dictionary holding videos of each word. If the system does not find words in the dictionary, then the most suitable synonym replaces them. The system proposed by us is inventive as the current systems are bound to direct conversion of words into Indian Sign Language on-the-other-hand our system aims to convert the sentences in Indian Sign Language grammar and effectively display it to the user.