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Results: 5
Number of items: 5
  • Open Access
    Pouw, C., Alishahi, A., & Zuidema, W. (2025). A Linguistically Motivated Analysis of Intonational Phrasing in Text-to-Speech Systems: Revealing Gaps in Syntactic Sensitivity. In G. Boleda, & M. Roth (Eds.), The 29th Conference on Computational Natural Language Learning (CoNLL 2025) : Proceedings of the Conference: CoNLL 2025 : July 31-August 1, 2025 (pp. 126-140). Association for Computational Linguistics. https://doi.org/10.18653/v1/2025.conll-1.9
  • Open Access
    López, L., Laanen, R., Pouw, C., & Parafita Couto, M. C. (2025). Remarks on the syntax of bare nouns in Papiamentu. Journal of Pidgin and Creole Languages, 40(2), 302-337. https://doi.org/10.1075/jpcl.00134.lop
  • Open Access
    de Heer Kloots, M., Mohebbi, H., Pouw, C., Shen, G., Zuidema, W., & Bentum, M. (2025). What do self-supervised speech models know about Dutch? Analyzing advantages of language-specific pre-training. Proceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH, 26, 256-260. https://doi.org/10.48550/arXiv.2506.00981, https://doi.org/10.21437/Interspeech.2025-1526
  • de Heer Kloots, M., Mohebbi, H., Pouw, C., Shen, G., Zuidema, W., & Bentum, M. (2025, May 29). SSL-NL dataset [Data set]. Zenodo. https://doi.org/10.5281/zenodo.15548946
  • Open Access
    Jumelet, J., Hanna, M., de Heer Kloots, M., Langedijk, A., Pouw, C., & van der Wal, O. (2023). ChapGTP, ILLC’s Attempt at Raising a BabyLM: Improving Data Efficiency by Automatic Task Formation. In A. Warstadt, A. Mueller, L. Choshen, E. Wilcox, C. Zhuang, J. Ciro, R. Mosquera, B. Paranjabe, A. Williams, T. Linzen, & R. Cotterell (Eds.), Findings of the BabyLM Challenge: Sample-efficient pretraining on developmentally plausible corpora (pp. 74-85). Association for Computational Linguistics. https://doi.org/10.18653/v1/2023.conll-babylm.6
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