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On the Inference Calibration of Neural Machine Translation

Contents

Introduction

This is the implementation of our work 'On the Inference Calibration of Neural Machine Translation'.

@inproceedings{Wang:2020:ACL,
    title = "On the Inference Calibration of Neural Machine Translation",
    author = "Wang, Shuo and Tu, Zhaopeng and Shi, Shuming and Liu, Yang",
    booktitle = "ACL",
    year = "2020"
}

Prerequisites

TER COMpute Java code

Download the TER tool from http://www.cs.umd.edu/%7Esnover/tercom/. We use TER label to calculate the inference ECE.

Usage

  1. Set the necessary paths in run.sh:
CODE=Path_to_InfECE
TER=Path_to_tercom-0.7.25
ref=Path_to_reference
hyp=Path_to_hypothesis
vocab=Path_to_target_side_vocabulary

Note that you need to save the token-level probabilities of ${hyp} in the file ${hyp}.conf, here is an example:

# hyp
I like music .
Do you like music ?
# hyp.conf
0.3 0.4 0.5 0.6
0.2 0.3 0.4 0.5 0.6
  1. Run run.sh to calculate the inference ECE:
./run.sh

Contact

If you have questions, suggestions and bug reports, please email wangshuo18@mails.tsinghua.edu.cn.

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