scholarly journals Multimedia Network English Reading Teaching Model Based on Speech Recognition Confidence Learning Algorithm

2021 ◽  
Vol 2021 ◽  
pp. 1-9 ◽  
Author(s):  
Chuanju Wang
Keyword(s):  
Speech Recognition ◽  
Learning Algorithm ◽  
Principal Component ◽  
Learning System ◽  
Svm Classifier ◽  
Communication Tool ◽  
English Teaching ◽  
English Reading ◽  
Multimedia Network ◽  
Reading Teaching

With deepening internationalization, English has become an increasingly important communication tool. Because traditional English teaching has short teacher-student interaction time, lack of oral English training environment, and single learning method, the oral English teaching is not ideal, and the students’ “speaking” confidence is insufficient. Aimed at addressing the exposed problems of traditional English reading teaching, this paper proposes a multimedia-based English reading teaching mode. On this basis, establish a voice recognition phoneme network grid to detect the recognition results. Secondly, the lattice is used to generate the confusion network mesh, and the acoustic posterior probability is calculated. Then, the feature vector is input into the SVM classifier for confidence mark, and finally the feature is extracted by principal component analysis. The research shows that multimedia network teaching can teach more vividly, increasing the initiative of students. At the same time, it is shown that the speech recognition confidence learning algorithm can improve the language learning system.

scholarly journals A Study on Improving ESP English Reading Ability for Students Major in Mechanical Design and Manufacturing

2021 ◽  
Vol 271 ◽  
pp. 04017
Author(s):  
Juan Du
Keyword(s):  
Reading Ability ◽  
English Language ◽  
Teaching Method ◽  
Mechanical Design ◽  
English Language Teaching ◽  
English Teaching ◽  
English Reading ◽  
Design And Manufacturing ◽  
Innovative Thinking ◽  
Reading Teaching

ESP Teaching method is an approach that is significantly different from the conventional English Language Teaching method. ESP teaching is a market-driven, communicative English teaching model which is based on the overall principle of significantly improving learners' professional English social skills, learnercentered, and meets the needs of society and individuals. In this study, researcher’s attempt is to integrate ESP reading model into the design and manufacturing English teaching. The study aims to explores the effect of ESP reading in mechanical design and manufacturing English teaching from the following three points, preclass reading task detection, while-reading teaching and post-reading teaching. And the author finds that ESP reading model not only make students have a strong interest in English learning and reading, improve their English reading ability and application ability of professional knowledge, but also enhance their innovative thinking ability.

scholarly journals A Spoken English Teaching System Based on Speech Recognition and Machine Learning

2021 ◽  
Vol 16 (14) ◽  
pp. 68
Author(s):  
Fengming Jiao ◽  
Jiao Song ◽  
Xin Zhao ◽  
Ping Zhao ◽  
Ru Wang
Keyword(s):  
Machine Learning ◽  
Speech Recognition ◽  
Error Detection ◽  
English Learners ◽  
Teaching Method ◽  
Learning Algorithm ◽  
Support Vector ◽  
Teaching System ◽  
English Teaching ◽  
Spoken English

The learning model and environment are two major constraints on spoken English learning by Chinese learners. The maturity of computer-aided language learning brings a new opportunity to spoken English learners. Based on speech recognition and machine learning, this paper designs a spoken English teaching system, and determines the overall architecture and functional modules of the system according to the system’s functional demand. Specifically, MATLAB was adopted to realize speech recognition, and generate a speech recognition module. Combined with machine learning algorithm, a deep belief network (DBN)-support vector machine (SVM) model was proposed to classify and detect the errors in pronunciation; the module also scores the quality and corrects the errors in pronunciation. This model was extended to a speech evaluation module was created. Next, several experiments were carried out to test multiple attributes of the system, including the accuracy of pronunciation classification and error detection, recognition rates of different environments and vocabularies, and the real-timeliness of recognition. The results show that our system achieved good performance, realized the preset design goals, and satisfied the user demand. This research provides an important theoretical and practical reference to transforming English teaching method, and improving the spoken English of learners.

A multimedia network English listening teaching model based on confidence learning algorithm of speech recognition

2021 ◽  
pp. 002072092098467
Author(s):  
Yubing Yao ◽  
Congying Ma
Keyword(s):  
Speech Recognition ◽  
Posterior Probability ◽  
Learning Algorithm ◽  
Confidence Score ◽  
Posteriori Probability ◽  
Support Vector ◽  
Teaching Model ◽  
Network Technology ◽  
Model Based ◽  
Multimedia Network

Language is the most important communication tool of human beings, and listening is one of the basic skills of language expression. Without good listening comprehension ability, it is impossible to use language flexibly to communicate. Due to the influence of traditional education mode, Chinese students' English listening is generally poor. Therefore, a new English listening teaching mode is needed to help students improve their English listening. In this paper, multimedia network technology is used to realize the integrated English listening teaching of listening, speaking and dictation skills, and a multimedia network English listening teaching model based on speech recognition confidence learning algorithm is proposed. In order to improve the effectiveness of the mainstream confidence method based on Lattice posterior probability, this paper proposes an improved confidence algorithm based on Lattice posterior probability, and then converts the obtained confidence score into discriminant confidence score by Support Vector Machine(SVM) to further enhance the discriminant ability of confidence. Aiming at the imbalance of training data, a score correction strategy is proposed. The experiment shows that the English listening teaching model realized by using multimedia network technology can effectively enhance the students interest in learning and improve their listening ability. And the improvement of the mainstream confidence method based on Lattice posteriori probability can effectively improve the recognition ability of the algorithm and further improve the students’ English listening learning effect.

scholarly journals Optimization of English Online Learning Dictionary System Based on Multiagent Architecture

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Ying Wang
Keyword(s):  
Online Learning ◽  
English Learners ◽  
English Language ◽  
Learning Algorithm ◽  
System Optimization ◽  
Learning System ◽  
English Learning ◽  
Communication Tool ◽  
Navigation Problem ◽  
Traditional System

As a universal language in the world, English has become a necessary language communication tool under the globalization of trade. Intelligent, efficient, and reasonable English language-assisted learning system helps to further improve the English ability of language learners. English online learning dictionary, as an important query tool for English learners, is an important part of English online learning. This paper will optimize the design of English online learning dictionary system based on multiagent architecture. Based on the hybrid multiagent cooperative algorithm, this paper will improve the disadvantages of the online English learning dictionary system and propose an appropriate dictionary application evaluation function. At the same time, an improved reinforcement learning algorithm is introduced into the corresponding English online learning dictionary navigation problem so as to improve the efficiency of the online English learning dictionary system. English online learning dictionary is more intelligent and efficient. In this paper, the new online learning dictionary system optimization algorithm is proposed and compared with the traditional system algorithm. The experimental results show that the algorithm proposed in this paper solves the collaborative confusion problem of English learning online dictionary to a certain extent and further solves the corresponding navigation problem so as to improve the efficiency.

Face Recognition using Segmental Euclidean Distance

2011 ◽  
Vol 61 (5) ◽  
pp. 431 ◽  
Author(s):  
Farrukh Sayeed ◽  
Madasu Hanmandlu ◽  
Abdul Quaiyum Ansari
Keyword(s):  
Euclidean Distance ◽  
Learning Algorithm ◽  
Recognition Rate ◽  
Principal Component ◽  
Support Vector ◽  
Svm Classifier ◽  
Test Image ◽  
Integral Image ◽  
Fuzzy Features ◽  
The Face

<p>In this paper an attempt has been made to detect the face using the combination of integral image along with the cascade structured classifier which is built using Adaboost learning algorithm. The detected faces are then passed through a filtering process for discarding the non face regions. They are individually split up into five segments consisting of forehead, eyes, nose, mouth and chin. Each segment is considered as a separate image and Eigenface also called principal component analysis (PCA) features of each segment is computed. The faces having a slight pose are also aligned for proper segmentation. The test image is also segmented similarly and its PCA features are found. The segmental Euclidean distance classifier is used for matching the test image with the stored one. The success rate comes out to be 88 per cent on the CG(full) database created from the databases of California Institute and Georgia Institute. However the performance of this approach on ORL(full) database with the same features is only 70 per cent. For the sake of comparison, DCT(full) and fuzzy features are tried on CG and ORL databases but using a well known classifier, support vector machine (SVM). Results of recognition rate with DCT features on SVM classifier are increased by 3 per cent over those due to PCA features and Euclidean distance classifier on the CG database. The results of recognition are improved to 96 per cent with fuzzy features on ORL database with SVM.</p><p><strong>Defence Science Journal, 2011, 61(5), pp.431-442</strong><strong><strong>, DOI:http://dx.doi.org/10.14429/dsj.61.1178</strong></strong></p>

The Application Research of Network Resources in English Reading Teaching

2014 ◽  
Vol 687-691 ◽  
pp. 2502-2505
Author(s):  
Li Na Wu ◽  
Tao Hua Xiao
Keyword(s):  
Network Resources ◽  
College English ◽  
English Teaching ◽  
Network Education ◽  
English Reading ◽  
The Status ◽  
Important Direction ◽  
Teaching Pattern ◽  
Reading Teaching ◽  
Current Database

With the advent of economic globalization, social informatization, foreign languages, especially English, has become one of the important tool of the communication with China's opening to the outside world. Social education in English teaching level has been more and more demanding. Therefore, how to improve and raise the level of the existing English teaching pattern is discussed, tested and tried in a variety of people. Among them, the network education is one of the important direction. This paper reviews the current database imperfect behind the status quo of college English reading, and put forward the use of network resources to establish a modern, fast and convenient new database of college English reading, and develop a platform for English reading.

scholarly journals The Effects of the CALL Model on College English Reading Teaching

2017 ◽  
Vol 12 (12) ◽  
pp. 24
Author(s):  
Dan Zhang ◽  
Xiaoying Wang
Keyword(s):  
College Students ◽  
Reading Ability ◽  
Theory And Practice ◽  
Computer Assisted ◽  
Important Indicator ◽  
College English ◽  
English Teaching ◽  
Advantages And Disadvantages ◽  
English Reading ◽  
Reading Teaching

Computer Assisted Language Learning (CALL) is an important concept in English teaching method reform. College students’ English reading ability is an important indicator in the evaluation on the college students’ English proficiency. Therefore, this paper applies the CALL model in English reading teaching. Firstly, it introduces the application and development prospect of the CALL model, and analyzes its advantages and disadvantages; secondly, it analyzes the present situation of college English teaching and its influencing factors and then designs an application example to integrate the CALL model with different aspect of English reading. Finally, it analyzes the teaching results of college English reading under the CALL model. Therefore, in both theory and practice, this paper proves the effectiveness and innovativeness of the CALL model.

Design of English reading and learning management system in college education based on artificial intelligence

2021 ◽  
pp. 1-10
Author(s):  
Fen Zhang ◽  
Min She
Keyword(s):  
Artificial Intelligence ◽  
Model Performance ◽  
College Education ◽  
Personalized Learning ◽  
Learning System ◽  
Model Function ◽  
English Reading ◽  
Function Modules ◽  
Learning Platforms ◽  
Learning Management

English reading learning in college education is an efficient means of English learning. However, most of the current English reading learning platforms in colleges and universities only put different English books on the platform in electronic form for students to read, which leads to blindness of reading. Based on artificial intelligence algorithms, this paper builds model function modules according to the needs of English reading and learning management in college education and implements system functions based on artificial intelligence algorithms. Moreover, according to the above design principles of personalized learning model and the characteristics of personalized network learning, this paper designs a personalized learning system based on meaningful learning theory. In addition, this article verifies and analyzes the model performance. The research results show that the model proposed in this paper has a certain effect.

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