Keyword Detection of Japanese Media Teaching Based on Support Vector Machines and Speech Detection
Mobile Information Systems, ISSN: 1875-905X, Vol: 2022, Page: 1-9
2022
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Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Article Description
The keyword detection of Japanese speech in streaming media has a certain effect on our study of Japanese information and a certain promotion effect on Japanese teaching. Currently, there is a problem of stability in the detection model of Japanese speech keywords. In order to improve the detection effect of Japanese speech keywords in streaming media, based on SVM, this study constructed a detection model of Japanese speech keywords in streaming media based on support vector machine. Moreover, this study analyzes the problem of SVM probability output and the comprehensive problem of SVM confidence, etc. In addition, by comparing the effect of confidence synthesis with the arithmetic average method, we found that the confidence obtained by SVM can obtain a higher recognition rate under the same rejection rate and improve the overall performance of the system. Finally, this study uses the difference comparison test to analyze the performance of the model proposed in this study. The research results show that the algorithm proposed in this paper has good performance and can be used as a follow-up system algorithm.
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