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        <title>Applicability of Pretrained Language Models: Automatic Screening for Children’s Language Development Level</title>
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    <abstract>The various potential of children can be limited by language delay or language impairments. However, there are many instances where parents are unaware of the child’s condition and do not obtain appropriate treatment as a result. Additionally, experts collecting children’s utterance to establish norms of language tests and evaluating children’s language development level takes a significant amount of time and work. To address these issues, dependable automated screening tools are required. In this paper, we used pretrained LM to assist experts in quickly and objectively screening the language development level of children. Here, evaluating the language development level is to ensure that the child has the appropriate language abilities for his or her age, which is the same as the child’s age. To do this, we analyzed the utterances of children according to age. Based on these findings, we use the standard deviations of the pretrained LM’s probability as a score for children to screen their language development level. The experiment results showed very strong correlations between our proposed method and the Korean language test REVT (REVT-R, REVT-E), with Pearson correlation coefficient of 0.9888 and 0.9892, respectively.</abstract>
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%0 Conference Proceedings
%T Applicability of Pretrained Language Models: Automatic Screening for Children’s Language Development Level
%A Oh, Byoung-doo
%A Lee, Yoon-koung
%A Kim, Yu-seop
%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 oh-etal-2022-applicability
%X The various potential of children can be limited by language delay or language impairments. However, there are many instances where parents are unaware of the child’s condition and do not obtain appropriate treatment as a result. Additionally, experts collecting children’s utterance to establish norms of language tests and evaluating children’s language development level takes a significant amount of time and work. To address these issues, dependable automated screening tools are required. In this paper, we used pretrained LM to assist experts in quickly and objectively screening the language development level of children. Here, evaluating the language development level is to ensure that the child has the appropriate language abilities for his or her age, which is the same as the child’s age. To do this, we analyzed the utterances of children according to age. Based on these findings, we use the standard deviations of the pretrained LM’s probability as a score for children to screen their language development level. The experiment results showed very strong correlations between our proposed method and the Korean language test REVT (REVT-R, REVT-E), with Pearson correlation coefficient of 0.9888 and 0.9892, respectively.
%R 10.18653/v1/2022.nlp4pi-1.18
%U https://aclanthology.org/2022.nlp4pi-1.18
%U https://doi.org/10.18653/v1/2022.nlp4pi-1.18
%P 149-156

Markdown (Informal)

[Applicability of Pretrained Language Models: Automatic Screening for Children’s Language Development Level](https://aclanthology.org/2022.nlp4pi-1.18) (Oh et al., NLP4PI 2022)

• Applicability of Pretrained Language Models: Automatic Screening for Children’s Language Development Level (Oh et al., NLP4PI 2022)

ACL

• Byoung-doo Oh, Yoon-koung Lee, and Yu-seop Kim. 2022. Applicability of Pretrained Language Models: Automatic Screening for Children’s Language Development Level. In Proceedings of the Second Workshop on NLP for Positive Impact (NLP4PI), pages 149–156, Abu Dhabi, United Arab Emirates (Hybrid). Association for Computational Linguistics.