This automatically-generated file contains references from the main union bibliography that have been filtered for a single tag. Do not edit this file; instead, please update the main bibliography and tag references appropriately to have them show up here. Thank you!
The papers are listed in the same order as the main bibliography; e.g., by year of publication / release; then by surname / name of the first author.
- Markl, N., & Lai, C. (2021, April). Context-sensitive evaluation of automatic speech recognition: considering user experience & . In Proceedings of the First Workshop on Bridging Human–Computer Interaction and Natural Language Processing (pp. 34-40). [paper]
- Tan, S., & Joty, S. (2021). Code-Mixing on Sesame Street: Dawn of the Adversarial Polyglots. Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies. doi:10.18653/v1/2021.naacl-main.282 [paper
- Bird, S. (2020, December). Decolonising speech and language technology. In Proceedings of the 28th International Conference on Computational Linguistics (pp. 3504-3519). doi:10.18653/v1/2020.coling-main.313 [paper]
- Joshi, P., Santy, S., Budhiraja, A., Bali, K., & Choudhury, M. (2020). The state and fate of linguistic diversity and inclusion in the NLP world. In Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, Association for Computational Linguistics, 2020, 6282-6293. doi:10.18653/v1/2020.acl-main.560 [paper]
- Koenecke, A., Nam, A., Lake, E., Nudell, J., Quartey, M., Mengesha, Z., ... & Goel, S. (2020). Racial disparities in automated speech recognition. Proceedings of the National Academy of Sciences, 117(14), 7684-7689. [paper]
- Tan, S., Joty, S., Kan, M. Y., & Socher, R. (2020, July). It's Morphin'Time! Combating Linguistic Discrimination with Inflectional Perturbations. Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics. [paper]
- Tan, S., Joty, S., Varshney, L. R., & Kan, M. Y. (2020, November). Mind your inflections! Improving NLP for non-standard Englishes with Base-Inflection Encoding. Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP). [paper]
- Bender, E. M. (2019). The # benderrule: On naming the languages we study and why it matters. The Gradient, 14. [paper]
- Huang, X., & Paul, M. (2019, June). Neural user factor adaptation for text classification: Learning to generalize across author demographics. In Proceedings of the Eighth Joint Conference on Lexical and Computational Semantics (* SEM 2019) (pp. 136-146). [paper]
- Zmigrod, R., Mielke, S. J., Wallach, H., & Cotterell, R. (2019). Counterfactual data augmentation for mitigating gender stereotypes in languages with rich morphology. In Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics, pages 1651–1661, Florence, Italy. Association for Computational Linguistics. [paper]
- Jurgens, D., Tsvetkov, Y., & Jurafsky, D. (2017, July). Incorporating dialectal variability for socially equitable language identification. In Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers) (pp. 51-57). [paper]
- Tatman, R. (2017, April). Gender and dialect bias in YouTube’s automatic captions. In Proceedings of the First ACL Workshop on Ethics in Natural Language Processing (pp. 53-59). [paper]
- Hovy, D., & Søgaard, A. (2015, July). Tagging performance correlates with author age. In Proceedings of the 53rd annual meeting of the Association for Computational Linguistics and the 7th international joint conference on natural language processing (volume 2: Short papers) (pp. 483-488). [paper]
- Jørgensen, A., Hovy, D., & Søgaard, A. (2015, July). Challenges of studying and processing dialects in social media. In Proceedings of the workshop on noisy user-generated text (pp. 9-18). [paper]