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Please use this identifier to cite or link to this item: http://20.198.91.3:8080/jspui/handle/123456789/8840
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dc.contributor.advisorDas, Dipankar-
dc.contributor.authorDutta, Oindrila-
dc.date.accessioned2025-10-09T10:25:23Z-
dc.date.available2025-10-09T10:25:23Z-
dc.date.issued2022-
dc.date.submitted2022-
dc.identifier.otherDC3532-
dc.identifier.urihttp://20.198.91.3:8080/jspui/handle/123456789/8840-
dc.description.abstractSentiment analysis has evolved over the past few decades, most of the work in it revolved around textual sentiment analysis with text mining techniques. But audio sentiment analysis is still in a nascent stage in the research community. In this proposed research, we perform sentiment analysis on speaker-discriminated speech transcripts to detect the emotions of the individual speakers involved in the conversation. We analysed different techniques to perform speaker discrimination and sentiment analysis to find efficient algorithms to perform this task.en_US
dc.format.extent69 p.en_US
dc.language.isoenen_US
dc.publisherJadavpur University, Kolkata, West Bengalen_US
dc.subjectEmotion Analysisen_US
dc.subjectMusic Information Retrieval ,Sentiment Analysisen_US
dc.titleRIEA – Retrieval of information & emotion analysis of musicen_US
dc.typeTexten_US
dc.departmentJadavpur University . Department of Computer Technologyen_US
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