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| Main Authors: | , , , , |
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| Format: | Preprint |
| Published: |
2023
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2310.16119 |
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| _version_ | 1866910341219221504 |
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| author | Kobza, Ondřej Čuhel, Jan Gargiani, Tommaso Herel, David Marek, Petr |
| author_facet | Kobza, Ondřej Čuhel, Jan Gargiani, Tommaso Herel, David Marek, Petr |
| contents | We present our SocialBot -- Alquist~5.0 -- developed for the Alexa Prize SocialBot Grand Challenge~5. Building upon previous versions of our system, we introduce the NRG Barista and outline several innovative approaches for integrating Barista into our SocialBot, improving the overall conversational experience. Additionally, we extend our SocialBot to support multimodal devices. This paper offers insights into the development of Alquist~5.0, which meets evolving user expectations while maintaining empathetic and knowledgeable conversational abilities across diverse topics. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2310_16119 |
| institution | arXiv |
| publishDate | 2023 |
| record_format | arxiv |
| spellingShingle | Alquist 5.0: Dialogue Trees Meet Generative Models. A Novel Approach for Enhancing SocialBot Conversations Kobza, Ondřej Čuhel, Jan Gargiani, Tommaso Herel, David Marek, Petr Machine Learning Artificial Intelligence We present our SocialBot -- Alquist~5.0 -- developed for the Alexa Prize SocialBot Grand Challenge~5. Building upon previous versions of our system, we introduce the NRG Barista and outline several innovative approaches for integrating Barista into our SocialBot, improving the overall conversational experience. Additionally, we extend our SocialBot to support multimodal devices. This paper offers insights into the development of Alquist~5.0, which meets evolving user expectations while maintaining empathetic and knowledgeable conversational abilities across diverse topics. |
| title | Alquist 5.0: Dialogue Trees Meet Generative Models. A Novel Approach for Enhancing SocialBot Conversations |
| topic | Machine Learning Artificial Intelligence |
| url | https://arxiv.org/abs/2310.16119 |