用机器学习和语音分析创新交流理论教学

O. Such, R. Fabricius, M. Klimo, J. Juhár
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摘要

克劳德·香农在20世纪50年代的基础性工作为此后几十年的传播理论提供了方向。研究的重点是发展新的编码和解码技术,以便有效利用所有可用的带宽。随着互联网的出现,特别是互联网商务的出现,通信理论的安全方面变得更加重要。随着对这些问题的研究进入成熟阶段,传播理论教师面临的挑战是找到新颖的想法,新的应用和新的跨学科主题,以吸引学生,并为他们应对未来在工程职业生涯中遇到的挑战做好准备。在我们的论文中,我们建议将信息论与其他两个科学学科的新兴联系应用于教学:机器学习和语音分析。
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Innovating instruction of communication theory with machine learning and speech analysis
Foundational work of Claude Shannon in 1950's provided direction for theory of communication for many decades thereafter. Emphasis of research was on development of new coding and decoding techniques in order to make effective use of all available bandwidth. With the advent of Internet, and especially of Internet commerce, security aspects of communication theory became much more important. As research in these questions enters a mature stage, the challenge for teachers of communication theory is to find novel ideas, new applications and new interdisciplinary topics in order to engage students as well as to prepare them to tackle challenges they will encounter in their engineering careers later on. In our paper we propose to apply to teaching emerging connections of information theory with two other scientific disciplines: machine learning and analysis of speech.
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