Ipa and stout: Leveraging linguistic and source-based features for machine translation evaluation

9Citations
Citations of this article
80Readers
Mendeley users who have this article in their library.

Abstract

This paper describes the UPC submissions to the WMT14 Metrics Shared Task: UPCIPA and UPC-STOUT. These metrics use a collection of evaluation measures integrated in ASIYA, a toolkit for machine translation evaluation. In addition to some standard metrics, the two submissions take advantage of novel metrics that consider linguistic structures, lexical relationships, and semantics to compare both source and reference translation against the candidate translation. The new metrics are available for several target languages other than English. In the the official WMT14 evaluation, UPC-IPA and UPC-STOUT scored above the average in 7 out of 9 language pairs at the system level and 8 out of 9 at the segment level.

Cite

CITATION STYLE

APA

Gonzalez, M., Cedeno, A. B., & Marquez, L. (2014). Ipa and stout: Leveraging linguistic and source-based features for machine translation evaluation. In Proceedings of the Annual Meeting of the Association for Computational Linguistics (pp. 394–401). Association for Computational Linguistics (ACL). https://doi.org/10.3115/v1/w14-3351

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free