Utilising Digital Media as a Second Language (L2) Support: A Case Study on Netflix with Translation Applications

Türkmen, Burcu

doi:10.7906/indecs.18.4.6

Cited by 12 publications

(8 citation statements)

References 3 publications

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“…Literature [15] arranges the update sequence between service chains under the consideration of network resource constraints, so as to complete the update of the entire network state. Literature [16] uses an OpenNF or Split/Merge update mechanism to realize the update of a single service chain. Literature [17] is too coarse-grained to study the update sequence of the service chain, and it is difficult to minimize the update time of the network state.…”

Section: Related Workmentioning

confidence: 99%

English Education Translation System Based on 5G Network Virtualization

Hou

2022

Journal of Sensors

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In order to improve the effect of English education translation, this paper improves the 5G network virtualization algorithm and uses the typical correlation analysis method in data mining to extract the correlation relationship between the data content contained in the massive English translation user equipment. Furthermore, this paper adopts the similarity-based clustering method to realize the self-organization construction of English translation virtual community. On this basis, this paper proposes a spectrum allocation algorithm based on convex optimization, which effectively solves the problem of spectrum allocation in virtual cells. Finally, this paper constructs the functional architecture of the English education translation system based on 5G network virtualization and conducts experimental research. The experimental research results show that the English education translation system based on 5G virtualization constructed in this paper can play an important role in smart English teaching.

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Section: Related Workmentioning

confidence: 99%

English Education Translation System Based on 5G Network Virtualization

Hou

2022

Journal of Sensors

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“…Question photo search is that students can turn to the Internet when they encounter a question they cannot understand and get the correct answer quickly. However, due to various reasons such as the OCR technology of each company, the quality of the question bank, and the user's photo scene, many times it is not possible to search for the correct topic [9]. e online question-making function has a built-in massive question bank for students to practice, but the fly in the ointment is that most of the products provide students with questions that are not targeted, and students cannot avoid the pain of the sea of questions.…”

Section: Introductionmentioning

confidence: 99%

Intelligent English Translation Based on Intelligent Speech Waveform Analysis

Meng

2022

Mobile Information Systems

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In order to improve the effectiveness of an intelligent English translation, this paper combines intelligent speech waveform technology to construct an intelligent English translation system. When the modulation method of each signal component is known, this paper takes the overlapping point as the fitting point set and performs fitting with each data point. Moreover, this paper takes the obtained modulation method parameters as eigenvectors and finally performs clustering to obtain the parameter estimation of each single-component signal. In addition, in the case of overlapping points between each linear English speech waveform dataset, this paper finds the overlapping points and processes the overlapping point sets. The simulation test and data statistical analysis results show that the intelligent English translation method based on intelligent speech waveform analysis proposed in this paper can effectively improve the effect of English translation.

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“…Object detection is the basic method of objectlevel analysis, and it has also entered a stage of rapid development. In the past ten years, the traditional machine intelligence translation field usually uses feature descriptors for object recognition tasks, and the progress is slow [15]. Due to the excellent performance of convolutional neural networks on ImageNet, the literature [16] general-ized the ability of AlexNet to recognize objects based on ImageNet training to the field of object detection, which is transfer learning.…”

Section: Related Workmentioning

confidence: 99%

Design and Application of Chinese English Machine Translation Model Based on Improved Bidirectional Neural Network Fusion Attention Mechanism

Qin

2022

Wireless Communications and Mobile Computing

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In order to improve the effect of Chinese-English machine translation, this paper combines attention mechanism and neural network algorithm and applies it to Chinese-English machine learning translation. Moreover, this paper uses Gaussian distribution instead of chi-square distribution to analyze the approximate error introduced by the Chinese and English speech energy detection method. In addition, this paper studies the overall and specific approximation errors by establishing the normalized mean square error function and the absolute error function, respectively. Finally, this paper proposes a new model for machine translation based on logarithmic position representation and self-attention mechanism. Through the experimental research, it can be seen that the Chinese-English machine translation model integrating attention mechanism and bidirectional neural network proposed in this paper has a good practical translation effect.

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Utilising Digital Media as a Second Language (L2) Support: A Case Study on Netflix with Translation Applications

Cited by 12 publications

References 3 publications

English Education Translation System Based on 5G Network Virtualization

English Education Translation System Based on 5G Network Virtualization

Intelligent English Translation Based on Intelligent Speech Waveform Analysis

Design and Application of Chinese English Machine Translation Model Based on Improved Bidirectional Neural Network Fusion Attention Mechanism

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