In every aspect of human life, sound plays an important role. From personal security to critical surveillance, sound is a key element to develop the automated systems for these fields. Few systems are already in the market, but their efficiency is a point of concern for their implementation in real-life scenarios. The learning capabilities of the deep learning architectures can be used to develop the sound classification systems to overcome efficiency issues of the traditional systems. Our aim, in this paper, is to use the deep learning networks for classifying the environmental sounds based on the generated spectrograms of these sounds. We used the spectrogram images of environmental sounds to train the convolutional neural network (CNN) and the tensor deep stacking network (TDSN). We used two datasets for our experiment: ESC-10 and ESC-50. Both systems were trained on these datasets, and the achieved accuracy was 77% and 49% in CNN and 56% in TDSN trained on the ESC-10. From this experiment, it is concluded that the proposed approach for sound classification using the spectrogram images of sounds can be efficiently used to develop the sound classification and recognition systems. INDEX TERMS Deep learning, convolutional neural network, tensor deep stacking networks, spectrograms.

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Multimedia-based technologies have significant impact on our daily life learning activities as they have shifted the education from teacher centered to learner centered. E-learning provides opportunities to people to take course online and provide a virtual classroom environment on the web through teacher learner interactions, course material distribution based on interactive multimedia. Interactive multimedia offers learners different forms of media to match their learning style, provides personalization of adaptive content delivery which enhanced learners learning effectiveness. In this chapter, we have discussed how information quality can be improved by multimedia based authoring tools and approaches, also identified the negative and positive effects of using interactive multimedia for learners in E-learning. Finally, focus was given on current E-learning multimedia technologies, their research challenges and future trends on social networking based technologies.

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