Abstract
As English is a widely used language in many countries of different cultures, variants of English also known as English creoles have also been created. Singlish is one such English creole used by people in Singapore. Nevertheless, unlike English, Singlish is not taught in schools nor encouraged to be used in formal communications. Hence, it remains to be a low resource language with a lack of up-to-date Singlish word dictionary and computational tools to analyse the language. In this paper, we therefore propose Singlish Checker, a tool that is able to help detecting Singlish text, Singlish words and phrases. To develop this tool, we first construct a large set of Singlish words and phrases by identifying different sources of Singlish words and their definitions and integrating them. We later propose a Singlish classifier model based on a BERT model fine-tuned with a large number of classified Singlish sentences. Our experiment show that the BERT-based classifier can achieved very high F1 performance, outperforming the baseline.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Zanelim/singbert. hugging face. https://huggingface.co/zanelim/singbert,. Accessed 31 Dec 2010
Botha, W.: A social network approach to particles in Singapore English. World Englishes 37(2), 261–281 (2018)
Chow, S.Y., Bond, F.: Singlish where got rules one? constructing a computational grammar for Singlish. In: LREC (2022)
Chua, H.: Stylistic approaches to predicting Reddit popularity in diglossia. In: ACL (2021). https://doi.org/10.18653/v1/2021.acl-srw.10
Devlin, J., Chang, M.W., Lee, K., Toutanova, K.: BERT: pre-training of deep bidirectional transformers for language understanding. arXiv preprint arXiv:1810.04805 (2018)
Gupta, A.F.: Singlish on the web. In: Varieties of English in South East Asia and Beyond, pp. 19–37. University of Malaya Press (2006)
Ho, D., Hamzah, D., Poria, S., Cambria, E.: Singlish SenticNet: a concept-based sentiment resource for Singapore English. In: 2018 IEEE Symposium Series on Computational Intelligence (SSCI), pp. 1285–1291 (2018)
Leow, Y.S., Lo, S.L.: Singlish polarity study using deep learning. In: First International Workshop on Social Media Analytics for Smart Cities (SMASC) (2017)
Lo, S.L., Cambria, E., Chiong, R., Cornforth, D.: A multilingual semi-supervised approach in deriving Singlish sentic patterns for polarity detection. Knowl.-Based Syst. 105, 236–247 (2016). https://doi.org/10.1016/j.knosys.2016.04.024
Sanh, V., Debut, L., Chaumond, J., Wolf, T.: Distilbert, a distilled version of BERT: smaller, faster, cheaper and lighter. In: NeurIPS EMC2 Workshop (2019)
Silva, A., Lo, P.C., Lim, E.P.: On predicting personal values of social media users using community-specific language features and personal value correlation. In: ICWSM, pp. 680–690 (2021)
Wang, H., Yang, J., Zhang, Y.: From genesis to creole language: transfer learning for Singlish universal dependencies parsing and POS tagging. ACM Trans. Asian Low-Resour. Lang. Inf. Process. 19(1), 1–29 (2019)
Wang, H., Zhang, Y., Chan, G.L., Yang, J., Chieu, H.L.: Universal Dependencies parsing for colloquial Singaporean English. In: ACL (2017). https://doi.org/10.18653/v1/P17-1159
Wong, J.: “Why you so Singlish one?” a semantic and cultural interpretation of the Singapore English particle one. Lang. Soc. 34(2), 239–275 (2005)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2022 The Author(s), under exclusive license to Springer Nature Switzerland AG
About this paper
Cite this paper
Hsieh, LH., Chua, NC., Kwee, A.T., Lo, PC., Lee, YY., Lim, EP. (2022). Singlish Checker: A Tool for Understanding and Analysing an English Creole Language. In: Tseng, YH., Katsurai, M., Nguyen, H.N. (eds) From Born-Physical to Born-Virtual: Augmenting Intelligence in Digital Libraries. ICADL 2022. Lecture Notes in Computer Science, vol 13636. Springer, Cham. https://doi.org/10.1007/978-3-031-21756-2_9
Download citation
DOI: https://doi.org/10.1007/978-3-031-21756-2_9
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-031-21755-5
Online ISBN: 978-3-031-21756-2
eBook Packages: Computer ScienceComputer Science (R0)