Update README.md

README.md

@@ -4,7 +4,7 @@ license: mit
 ABX-accent
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-The ABX-accent project is based on the preparation and evaluation of the Accented English Speech Recognition Challenge (AESRC) dataset [1], using ABXpy for evaluation [2][3]. This repository provides all the necessary tools and resources to carry out both dataset preparation and evaluation.
+The ABX-accent project is based on the preparation and evaluation of the Accented English Speech Recognition Challenge (AESRC) dataset [1], using fastABX[2] for evaluation. This repository provides all the necessary tools and resources to carry out both dataset preparation and evaluation.
 
 What is ABX Evaluation?
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@@ -27,6 +27,4 @@ References
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 - [1] Xian Shi, Fan Yu, Yizhou Lu, Yuhao Liang, Qiangze Feng, Daliang Wang, Yanmin Qian, and Lei Xie, “The accented english speech recognition challenge 2020: open datasets, tracks, baselines, results and methods,” in ICASSP 2021-2021 IEEE International Conference on Acoustics, Speech and Signal Processing       (ICASSP).IEEE, 2021, pp. 6918–6922.
   
-- [2] Ewan Dunbar, Julien Karadayi, Mathieu Bernard, Xuan-Nga Cao, Robin Algayres, Lucas Ondel, Laurent Besacier, Sakriani Sakti, and Emmanuel Dupoux, “The zero resource speech challenge 2020: Discovering discrete subword and word units,” 2020.
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-- [3] Ewan Dunbar, Mathieu Bernard, Nicolas Hamilakis, Tu Anh Nguyen, Maureen de Seyssel, Patricia Roz ́e, Morgane Rivi`ere, Eugene Kharitonov, and Emmanuel Dupoux, “The zero resource speech challenge 2021: Spoken language modelling,” 2021.
+- [2] Maxime Poli, Emmanuel Chemla, Emmanuel Dupoux "fastabx: A library for efficient computation of ABX discriminability" arXiv:2505.02692v1 [cs.CL] 5 May 2025.