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<title>Year-2020</title>
<link>http://repository.iiitd.edu.in/xmlui/handle/123456789/971</link>
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<dc:date>2026-04-11T19:04:14Z</dc:date>
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<title>Multimodal multi-speaker merger &amp; acquisition (M3A) financial forecasting: a new task, dataset, and neural baselines</title>
<link>http://repository.iiitd.edu.in/xmlui/handle/123456789/997</link>
<description>Multimodal multi-speaker merger &amp; acquisition (M3A) financial forecasting: a new task, dataset, and neural baselines
Goel, Prakhar; Goyal, Mihir; Shah, Rajiv Ratn (Advisor)
Financial risk prediction is an essential task in today’s financial markets, especially with the disclosure of&#13;
important information such as Merger and Acquisition (M&amp;A) calls nowadays. M&amp;A calls often provide&#13;
key insights into the confidence levels and agreeability between the different high ranking members of&#13;
an organization concerning a merger or acquisition in the form of subtle vocal cues and verbal messages.&#13;
Variations in vocal features such as pitch can suggest doubt and a lack of confidence that may discredit&#13;
the message spoken. Additionally, information about the speaker of the message can assist the system&#13;
in making better predictions. To aid the analysis of M&amp;A calls, we curate a dataset of conference call&#13;
transcripts and audios from the past 5 years. We propose strong baseline architectures to accompany&#13;
the model that takes advantage of the multimodal multi-speaker input to perform financial forecasting.&#13;
Empirical results show the improvement that our architecture gives over existing models.
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<dc:date>2020-12-01T00:00:00Z</dc:date>
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<title>Online schooling during covid-19 era</title>
<link>http://repository.iiitd.edu.in/xmlui/handle/123456789/972</link>
<description>Online schooling during covid-19 era
Walia, Angel; Eden, Grace (Advisor)
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<dc:date>2020-12-01T00:00:00Z</dc:date>
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