E-learning provides an individualized course path which provides a user the convenience of pacing ones way through a particular course. One of the key privileges it offers is the flexibility of the course and consistent delivery of the material. The proposed system predicts the user’s domain knowledge with the help of the lectures knowledge that a particular user completes and also a lecture’s knowledge gets updated with respect to the users’ knowledge who searches for it. The dependency among the domains also plays a vital role in updating ones’ domain knowledge. The dependencies can be determined by constructing a fuzzy cognitive map. This helps in determining the user’s knowledge in other domains also. The lectures of the proposed system include Augmented Reality and Virtual Reality contents which give an interactive learning experience to the users. The user commands are accepted as audio signals, processed, classified and mapped to the system commands to make it to respond. This proposed work uses the combination of discrete wavelet transform and wavelet packet decomposition for feature extraction and artificial neural network for classification.

中文翻译：

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语音界面增强和虚拟现实内容在电子学习中的用户领域知识预测

电子学习提供了个性化的课程路径，为用户提供了在特定课程中按步调动的便利。它提供的主要特权之一是课程的灵活性和材料的一致交付。所提出的系统借助于特定用户完成的讲义知识来预测用户的领域知识，并且讲义知识相对于搜索它的用户知识而得到更新。领域之间的依赖性在更新领域知识方面也起着至关重要的作用。可以通过构造模糊认知图来确定依赖性。这也有助于确定用户在其他域中的知识。拟议系统的讲座包括增强现实和虚拟现实内容，这些内容为用户提供了交互式学习体验。用户命令被接受为音频信号，经过处理，分类并映射到系统命令以使其响应。这项工作结合了离散小波变换和小波包分解的特征提取和人工神经网络的分类。