# A Multilingual African Embedding for FAQ Chatbots

arXiv: https://arxiv.org/abs/2103.09185 · HTML: https://mlsanity.com/paper/2103.09185/

## Key facts

- Cited by 5 papers in the map (data through 14 Oct 2026).
- Builds on 3 of its 10 references that are in the map.
- First posted on arXiv 16 Mar 2021.

## Builds on (most cited first, 3 of 3)

- [Towards a Human-like Open-Domain Chatbot](https://mlsanity.com/paper/2001.09977/) (2020)
- [Neural Arabic Question Answering](https://mlsanity.com/paper/1906.05394/) (2019)
- [TUNIZI: a Tunisian Arabizi sentiment analysis Dataset](https://mlsanity.com/paper/2004.14303/) (2020)

## Built on by (most cited first, 5 of 5)

- [Natural Language Processing for Dialects of a Language: A Survey](https://mlsanity.com/paper/2401.05632/) (2024)
- [Charting the Landscape of African NLP: Mapping Progress and Shaping the Road Ahead](https://mlsanity.com/paper/2505.21315/) (2025)
- [KenSwQuAD -- A Question Answering Dataset for Swahili Low Resource Language](https://mlsanity.com/paper/2205.02364/) (2022)
- [Global Readiness of Language Technology for Healthcare: What would it Take to Combat the Next Pandemic?](https://mlsanity.com/paper/2204.02790/) (2022)
- [NaijaNLP: A Survey of Nigerian Low-Resource Languages](https://mlsanity.com/paper/2502.19784/) (2025)

## Abstract (arXiv)

Searching for an available, reliable, official, and understandable information is not a trivial task due to scattered information across the internet, and the availability lack of governmental communication channels communicating with African dialects and languages. In this paper, we introduce an Artificial Intelligence Powered chatbot for crisis communication that would be omnichannel, multilingual and multi dialectal. We present our work on modified StarSpace embedding tailored for African dialects for the question-answering task along with the architecture of the proposed chatbot system and a description of the different layers. English, French, Arabic, Tunisian, Igbo,Yor`ub'a, and Hausa are used as languages and dialects. Quantitative and qualitative evaluation results are obtained for our real deployed Covid-19 chatbot. Results show that users are satisfied and the conversation with the chatbot is meeting customer needs.