1 code implementation • 1 Apr 2024 • Vincent Fan, Yujie Qian, Alex Wang, Amber Wang, Connor W. Coley, Regina Barzilay
Our machine learning models attain state-of-the-art performance when evaluated individually, and we meticulously annotate a challenging dataset of reaction schemes with R-groups to evaluate our pipeline as a whole, achieving an F1 score of 69. 5%.
no code implementations • 9 Apr 2021 • Xiangyun Chu, Elizabeth Combs, Amber Wang, Michael Picheny
This paper explores methods that are inspired by human perception to evaluate possible performance improvements for recognition of accented speech, with a specific focus on recognizing speech with a novel accent relative to that of the training data.