An approach to unveiling personality trait classification from Bangla speeches of political leaders

dc.contributor.advisorAlam, Golam Rabiul
dc.contributor.authorPodder, Swachcha
dc.contributor.authorAlam, Ajfar
dc.contributor.authorRodela, Swoperjita Tanha Akond
dc.contributor.authorIsmail, Ishama Fatima
dc.date.accessioned2025-09-04T10:16:32Z
dc.date.available2025-09-04T10:16:32Z
dc.date.issued2025-06
dc.descriptionCataloged from PDF version of thesis.
dc.descriptionIncludes bibliographical references (pages 47-48).
dc.descriptionThis thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2025.
dc.description.abstractThe power of speech lies in its ability to communicate with people. Political speeches can influence people’s minds through their persuasive language. The general public needs to know about the political personnel and their actions. They have huge responsibilities surrounding different sectors such as the education sector, healthcare sector, etc., which affect people’s daily lives, and their future might depend on it too. Speech is a way for political leaders to express themselves, and through their speeches, we will be trying to decipher their personality traits. To comprehend the personality traits through the text samples, we use the NEO-FFI personality traits (Openness, Conscientiousness, Extroversion, Agreeableness, and Neuroticism) to determine the personality of a particular political person. In our research, we mainly focus on Bangla speeches, and the data is collected from various authentic platforms in the audio format, which is then converted to a transcript. Politicians effectively utilizing their speech can influence the opinions of the general public. So, political speeches are a great way to understand the leaders’ personalities by the general masses to be more conscious and vote wisely. A comparative analysis is shown between different statistical and transformer based classifiers that are used to show the performance after training the model on our primary dataset.
dc.identifier.otherID 21301196
dc.identifier.otherID 21301127
dc.identifier.otherID 21301117
dc.identifier.otherID 21301118
dc.identifier.otherhttps://dspace.bracu.ac.bd/server/api/core/items/15d816c4-d39d-4058-bd6e-95f98dd96049
dc.identifier.urihttp://hdl.handle.net/10361/26673
dc.language.isoen
dc.publisherBRAC University
dc.sourceBRAC University Institutional Repository
dc.subjectBangla speech
dc.subjectBangladesh political leaders
dc.subjectDeep learning
dc.subjectTransformers
dc.subjectAttentionbased mechanism
dc.titleAn approach to unveiling personality trait classification from Bangla speeches of political leaders
dc.typeThesis

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