@inproceedings{mahajan-2022-bela,
title = "{BELA}: Bot for {E}nglish Language Acquisition",
author = "Mahajan, Muskan",
editor = "Biester, Laura and
Demszky, Dorottya and
Jin, Zhijing and
Sachan, Mrinmaya and
Tetreault, Joel and
Wilson, Steven and
Xiao, Lu and
Zhao, Jieyu",
booktitle = "Proceedings of the Second Workshop on NLP for Positive Impact (NLP4PI)",
month = dec,
year = "2022",
address = "Abu Dhabi, United Arab Emirates (Hybrid)",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2022.nlp4pi-1.17",
doi = "10.18653/v1/2022.nlp4pi-1.17",
pages = "142--148",
abstract = "In this paper, we introduce a conversational agent (chatbot) for Hindi-speaking youth called BELA{---}Bot for English Language Acquisition. Developed for young underprivileged students at an Indian non-profit, the agent supports both Hindi and Hinglish (code-switched Hindi and English, written primarily with English orthography) utterances. BELA has two interaction modes: a question-answering mode for classic English language learning tasks like word meanings, translations, reading passage comprehensions, etc., and an open-domain dialogue system mode to allow users to practice their language skills. We present a high-level overview of the design of BELA, including the implementation details and the preliminary results of our early prototype. We also report the challenges in creating an English-language learning chatbot for a largely Hindi-speaking population.",
}
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<abstract>In this paper, we introduce a conversational agent (chatbot) for Hindi-speaking youth called BELA—Bot for English Language Acquisition. Developed for young underprivileged students at an Indian non-profit, the agent supports both Hindi and Hinglish (code-switched Hindi and English, written primarily with English orthography) utterances. BELA has two interaction modes: a question-answering mode for classic English language learning tasks like word meanings, translations, reading passage comprehensions, etc., and an open-domain dialogue system mode to allow users to practice their language skills. We present a high-level overview of the design of BELA, including the implementation details and the preliminary results of our early prototype. We also report the challenges in creating an English-language learning chatbot for a largely Hindi-speaking population.</abstract>
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%0 Conference Proceedings
%T BELA: Bot for English Language Acquisition
%A Mahajan, Muskan
%Y Biester, Laura
%Y Demszky, Dorottya
%Y Jin, Zhijing
%Y Sachan, Mrinmaya
%Y Tetreault, Joel
%Y Wilson, Steven
%Y Xiao, Lu
%Y Zhao, Jieyu
%S Proceedings of the Second Workshop on NLP for Positive Impact (NLP4PI)
%D 2022
%8 December
%I Association for Computational Linguistics
%C Abu Dhabi, United Arab Emirates (Hybrid)
%F mahajan-2022-bela
%X In this paper, we introduce a conversational agent (chatbot) for Hindi-speaking youth called BELA—Bot for English Language Acquisition. Developed for young underprivileged students at an Indian non-profit, the agent supports both Hindi and Hinglish (code-switched Hindi and English, written primarily with English orthography) utterances. BELA has two interaction modes: a question-answering mode for classic English language learning tasks like word meanings, translations, reading passage comprehensions, etc., and an open-domain dialogue system mode to allow users to practice their language skills. We present a high-level overview of the design of BELA, including the implementation details and the preliminary results of our early prototype. We also report the challenges in creating an English-language learning chatbot for a largely Hindi-speaking population.
%R 10.18653/v1/2022.nlp4pi-1.17
%U https://aclanthology.org/2022.nlp4pi-1.17
%U https://doi.org/10.18653/v1/2022.nlp4pi-1.17
%P 142-148
Markdown (Informal)
[BELA: Bot for English Language Acquisition](https://aclanthology.org/2022.nlp4pi-1.17) (Mahajan, NLP4PI 2022)
ACL
- Muskan Mahajan. 2022. BELA: Bot for English Language Acquisition. In Proceedings of the Second Workshop on NLP for Positive Impact (NLP4PI), pages 142–148, Abu Dhabi, United Arab Emirates (Hybrid). Association for Computational Linguistics.