LeagueBot: A Voice LLM Companion of Cognitive and Emotional Support for Novice Players in Competitive Games
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arXiv
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| Main Authors: | , , |
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| Format: | Preprint |
| Published: |
2026
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| _version_ | 1866908802777874432 |
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| author | Lee, Jungmin Cho, Inhee Yoo, Youngjae |
| author_facet | Lee, Jungmin Cho, Inhee Yoo, Youngjae |
| contents | Competitive games pose steep learning curves and strong social pressures, often discouraging novice players and limiting sustained engagement. To address these challenges, this study introduces LeagueBot, a large language model-based voice chatbot designed to provide both informational and emotional support during live gameplay in league of legends, one of the most competitive multiplayer online battle arena games. In a within-subjects experiment with 33 novice players, LeagueBot was found to reduce cognitive challenge, performative challenge, and perceived tension. Qualitative analysis further identified three themes: enhanced access to game information, relief from cognitive burden, and practical limitations. Participants noted that LeagueBot offered context-appropriate guidance and emotional support, helping ease the steep learning curve and psychological pressures of competitive gaming. Together, these findings underscore the potential of voice-based LLM companions to assist novice players in competitive environments and highlight their broader applicability for real-time support in other high-pressure contexts. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2602_01213 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | LeagueBot: A Voice LLM Companion of Cognitive and Emotional Support for Novice Players in Competitive Games Lee, Jungmin Cho, Inhee Yoo, Youngjae Human-Computer Interaction Competitive games pose steep learning curves and strong social pressures, often discouraging novice players and limiting sustained engagement. To address these challenges, this study introduces LeagueBot, a large language model-based voice chatbot designed to provide both informational and emotional support during live gameplay in league of legends, one of the most competitive multiplayer online battle arena games. In a within-subjects experiment with 33 novice players, LeagueBot was found to reduce cognitive challenge, performative challenge, and perceived tension. Qualitative analysis further identified three themes: enhanced access to game information, relief from cognitive burden, and practical limitations. Participants noted that LeagueBot offered context-appropriate guidance and emotional support, helping ease the steep learning curve and psychological pressures of competitive gaming. Together, these findings underscore the potential of voice-based LLM companions to assist novice players in competitive environments and highlight their broader applicability for real-time support in other high-pressure contexts. |
| title | LeagueBot: A Voice LLM Companion of Cognitive and Emotional Support for Novice Players in Competitive Games |
| topic | Human-Computer Interaction |
| url | https://arxiv.org/abs/2602.01213 |