Automatic Machine Translation Evaluation with Part-of-Speech Information

Han, Aaron Li-Feng; Wong, Derek F.; Chao, Lidia S.; He, Liangye

doi:10.1007/978-3-642-40585-3_16

Cited by 1 publication

(2 citation statements)

References 4 publications

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“…However, there are several fully Automatic Machine Translation Evaluation (AMTE) metrics. They can be classified into five categories [4]: lexical [31,23], character [30], semantic [18,24], syntactic [3,13,19,5], and semantic-syntactic metrics [7].…”

Section: State Of the Artmentioning

confidence: 99%

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Syntactic Quality Measurement in Machine Translation with Interlinguas

Maisto,

Oliver

2023

Proceedings of the International Conference on Human-Informed Translation and Interpreting Technology 2023

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The measurement of machine translation (MT) performances is an unsolved issue in NLP. This task can be done by a human but the time cost and the need for skilled workers to do it rise the necessity for automatic ways to measure the quality of a translation. In this work, we aim to develop a new methodology for measuring the quality of MT results from a syntactic point of view. The idea takes as a theoretical framework the work of Harris about the decomposition of sentences in elementary units called kernels. Our model parses Spanish sentences and UNL (Universal Networking Language) Graphs with a rule-based methodology and divides them into units of information.Comparing those units the model measures the quality of the translation. Our results show that decomposing the sentences in minimal syntactic units could improve the evaluation performances also without a lexical/semantic analysis.

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Section: State Of the Artmentioning

confidence: 99%

“…Among syntactic AMTE metrics, MaxSIM [3], Helpor [13] and HWCM [19] use dependency parsing and POS tags to compute the similarity between two sentences, overlooking semantic information. Guzman proposes to add discourse structures to the quality measure metrics [11].…”

Section: State Of the Artmentioning

confidence: 99%

Syntactic Quality Measurement in Machine Translation with Interlinguas

Maisto,

Oliver

2023

Proceedings of the International Conference on Human-Informed Translation and Interpreting Technology 2023

View full text Add to dashboard Cite

show abstract

Automatic Machine Translation Evaluation with Part-of-Speech Information

Cited by 1 publication

References 4 publications

Syntactic Quality Measurement in Machine Translation with Interlinguas

Syntactic Quality Measurement in Machine Translation with Interlinguas

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