Summary of Task-oriented Dialog Systems For the Senegalese Wolof Language, by Derguene Mbaye and Moussa Diallo
Task-Oriented Dialog Systems for the Senegalese Wolof Language
by Derguene Mbaye, Moussa Diallo
First submitted to arxiv on: 15 Dec 2024
Categories
- Main: Computation and Language (cs.CL)
- Secondary: Artificial Intelligence (cs.AI); Human-Computer Interaction (cs.HC); Information Retrieval (cs.IR)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary This paper proposes a modular architecture-based Task-oriented Dialog Systems (ToDS) approach for conversational agents. The authors highlight the limitations of large language models (LLMs), including hallucination and underrepresentation of low-resource languages like African ones. They present a chatbot generation engine based on Rasa framework and an in-house machine translation system to project annotations onto the Wolof language. Experimental results show that their approach performs similarly for French, a resource-rich language, and Wolof. The authors also demonstrate the extensibility of this approach to other low-resource languages. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This paper talks about special computers called chatbots. Right now, people are making big chatbots that can talk to humans, but they’re not very good at understanding some languages like African ones. The problem is that these big chatbots can make up fake information, which isn’t helpful. This paper shows a new way to build smaller chatbots that work better with the languages we need them to understand. They use special software and translation tools to make this happen. It looks like their approach works well for one African language called Wolof, and they think it could work for other languages too. |
Keywords
» Artificial intelligence » Hallucination » Translation
