@inproceedings{nunziatini-alfieri-2021-synthesis,
    title = "A Synthesis of Human and Machine: Correlating {\textquotedblleft}New{\textquotedblright} Automatic Evaluation Metrics with Human Assessments",
    author = "Nunziatini, Mara  and
      Alfieri, Andrea",
    editor = "Campbell, Janice  and
      Huyck, Ben  and
      Larocca, Stephen  and
      Marciano, Jay  and
      Savenkov, Konstantin  and
      Yanishevsky, Alex",
    booktitle = "Proceedings of Machine Translation Summit XVIII: Users and Providers Track",
    month = aug,
    year = "2021",
    address = "Virtual",
    publisher = "Association for Machine Translation in the Americas",
    url = "https://preview.aclanthology.org/add-emnlp-2024-awards/2021.mtsummit-up.29/",
    pages = "440--465",
    abstract = "The session will provide an overview of some of the new Machine Translation metrics available on the market, analyze if and how these new metrics correlate at a segment level to the results of Adequacy and Fluency Human Assessments, and how they compare against TER scores and Levenshtein Distance {--} two of our currently preferred metrics {--} as well as against each of the other. The information in this session will help to get a better understanding of their strengths and weaknesses and make informed decisions when it comes to forecasting MT production."
}