Denise Díaz

Also published as: Denise Diaz


2021

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Gender bias amplification during Speed-Quality optimization in Neural Machine Translation
Adithya Renduchintala | Denise Diaz | Kenneth Heafield | Xian Li | Mona Diab
Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 2: Short Papers)

Is bias amplified when neural machine translation (NMT) models are optimized for speed and evaluated on generic test sets using BLEU? We investigate architectures and techniques commonly used to speed up decoding in Transformer-based models, such as greedy search, quantization, average attention networks (AANs) and shallow decoder models and show their effect on gendered noun translation. We construct a new gender bias test set, SimpleGEN, based on gendered noun phrases in which there is a single, unambiguous, correct answer. While we find minimal overall BLEU degradation as we apply speed optimizations, we observe that gendered noun translation performance degrades at a much faster rate.

2020

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A Survey of Qualitative Error Analysis for Neural Machine Translation Systems
Denise Díaz | James Cross | Vishrav Chaudhary | Ahmed Kishky | Philipp Koehn
Proceedings of the 14th Conference of the Association for Machine Translation in the Americas (Volume 2: User Track)