基于阿拉伯文本的封装视频分类与检索

Reem Aljorani, Boshra F. Zopon
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引用次数: 0

摘要

由于阿拉伯语视频分类并不是一个热门的领域,在这方面的研究并不多,尤其是在教育领域。提出了一个系统来解决这个问题,并使学生更容易获得阿拉伯语教育视频。为了设计和实现一个系统,通过使用生成文本文本的azure认知服务提取音频特征来对阿拉伯语视频进行分类,我们完成了一项调查,研究了几篇论文。然后应用几个预处理操作来处理文本抄本。使用随机梯度下降SGD算法对转录本进行分类,并为每个视频给出合适的标签。此外,还应用了搜索技术,使学生能够检索他们需要的视频。结果表明,与其他学习模型相比,SGD算法的分类准确率最高,达到89.3%。在下面的部分中,介绍了一项由最相关和最新的论文组成的调查。
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Encapsulation Video Classification and Retrieval Based on Arabic Text
Since Arabic video classification is not a popular field and there isn’t a lot of researches in this area especially in the educational field. A system was proposed to solve this problem and to make the educational Arabic videos more available to the students. A survey was fulfilled to study several papers in order to design and implement a system that classifies videos operative in the Arabic language by extracting its audio features using azure cognitive services which produce text transcripts. Several preprocessing operations are then applied to process the text transcript. A stochastic gradient descent SGD algorithm was used to classify transcripts and give a suitable label for each video. In addition, a search technique was applied to enable students to retrieve the videos they need. The results showed that SGD algorithm recorded the highest classification accuracy with 89.3 % when compared to other learning models. In the section below, a survey was introduced consisting of the most relevant and recent papers to this work.
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