Abstract
In the era of Internet, there is a tremendous amount of textual and audio data spread all over the place, and it becomes very important to develop a method to fetch the most important information efficiently and quickly. Extracting summary manually is a very redundant and time-consuming process. A good summarizing technique is one where we discern all the important points and topics of a speech or document without leaving out any valuable information. Summarizing a speech without losing the actual context has always been a challenge for programmers for a long time. This paper explores a method to divide a large speech into multiple small speeches to summarize them individually to generate an efficient and precise summary. Each sub-speech is further processed to predict the emotion of the speaker at various points during the speech. These individual emotions are used to classify a generalized emotion of the speaker throughout the speech.
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Anand, A., Choudhary, H., Singhania, A., Manuraj, A., Jayashree, R. (2023). Topic-Wise Speech Summarization with Emotion Classification. In: Kumar, A., Ghinea, G., Merugu, S., Hashimoto, T. (eds) Proceedings of the International Conference on Cognitive and Intelligent Computing. Cognitive Science and Technology. Springer, Singapore. https://doi.org/10.1007/978-981-19-2358-6_39
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DOI: https://doi.org/10.1007/978-981-19-2358-6_39
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