Abstract
Speech information is a large part of the Internet data type, which represents many valuable resources in the real world. However, extracting topics of speech is much challenging because there is not only a requirement for an analyzation of multi-level speech data, but also a requirement for valid methods for filtering and displaying extraction results. Meanwhile, the time consumption is also an important factor. Our work provides a visualization system for analyzation and extraction of speech. By means of case studies of real-world speech data, the practicability and effectiveness of the method are demonstrated.
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Acknowledgements
The work is supported by the National Nature Science Foundation of China (61100053) and CCF-Venustech Hongyan Research Initiative (2016-013).
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Tang, X., Dong, X., Zhang, H. (2019). CWordle: A Visual Analytics System for Extracting the Topics of Speech. In: Bhatia, S., Tiwari, S., Mishra, K., Trivedi, M. (eds) Advances in Computer Communication and Computational Sciences. Advances in Intelligent Systems and Computing, vol 760. Springer, Singapore. https://doi.org/10.1007/978-981-13-0344-9_7
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DOI: https://doi.org/10.1007/978-981-13-0344-9_7
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