Datasets:
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Project Title: The KPL Multimodal Esports Commentary Dataset
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Abstract: This paper introduces a multimodal labeled dataset including 65 minutes and 24 seconds of commentary from three dynamic matches in the King Pro League (KPL) of the game "Honor of Kings": the 2021 Autumn Semifinals, 2025 Finals, and 2025 Summer Finals. This dataset was collected by extracting AI-generated, time-aligned transcripts from recording videos on BiliBili Platform, which combines essential manually modification to ensure accuracy. It features comprehensive manual annotations, including speaker recognition, screen event descriptions, domain-specific terminology (OOV) extraction, and emotion grading. Provided in CSV format, this dataset addresses the scarcity of high-intensity, domain-specific spoken language resources, offering significant potential for multimodal sentiment analysis and esports-related Natural Language Processing (NLP) research.
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---
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language:
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- zh
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task_categories:
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- text-classification
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- token-classification
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tags:
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- esports
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- multimodal
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- sentiment-analysis
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license: cc-by-4.0
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---
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Project Title: The KPL Multimodal Esports Commentary Dataset
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Abstract: This paper introduces a multimodal labeled dataset including 65 minutes and 24 seconds of commentary from three dynamic matches in the King Pro League (KPL) of the game "Honor of Kings": the 2021 Autumn Semifinals, 2025 Finals, and 2025 Summer Finals. This dataset was collected by extracting AI-generated, time-aligned transcripts from recording videos on BiliBili Platform, which combines essential manually modification to ensure accuracy. It features comprehensive manual annotations, including speaker recognition, screen event descriptions, domain-specific terminology (OOV) extraction, and emotion grading. Provided in CSV format, this dataset addresses the scarcity of high-intensity, domain-specific spoken language resources, offering significant potential for multimodal sentiment analysis and esports-related Natural Language Processing (NLP) research.
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