Madurese is one of the regional languages in Indonesia, which dominates East Java and Madura Island particular. The use as a daily language has declined significantly due to shift children adolescents, some are caused by sense prestige difficulty learning Madurese. scarcity research or scientific titles that raises also helps reduce literacy language. Our focuses on creating translation machine...

We present a method for finding oracle BLEU translations in phrase-based statistical machine translation using exact document-level scores. Experiments are presented where the BLEU score of a candidate translation is directly optimised in order to examine the properties of reachable translations with very high BLEU scores. This is achieved by running the documentlevel decoder Docent in BLEU-dec...

We present a method for finding oracle BLEU translations in phrase-based statistical machine translation using exact document-level scores. Experiments are presented where the BLEU score of a candidate translation is directly optimised in order to examine the properties of reachable translations with very high BLEU scores. This is achieved by running the documentlevel decoder Docent in BLEU-dec...

Neural network language models are often trained by optimizing likelihood, but we would prefer to optimize for a task specific metric, such as BLEU in machine translation. We show how a recurrent neural network language model can be optimized towards an expected BLEU loss instead of the usual cross-entropy criterion. Furthermore, we tackle the issue of directly integrating a recurrent network i...

BLEU is the de facto standard automatic evaluation metric in machine translation. While BLEU is undeniably useful, it has a number of limitations. Although it works well for large documents and multiple references, it is unreliable at the sentence or sub-sentence levels, and with a single reference. In this paper, we propose new variants of BLEU which address these limitations, resulting in a m...

We present a human judgements dataset and also an adapted metric for evaluation of Arabic machine translation. Our medium-scale dataset is first of its kind for Arabic with high annotation quality. We use the dataset to adapt the BLEU score for Arabic. Our score (AL-BLEU) provides partial credits for stem and morphological matchings of hypothesis and reference words. We evaluate BLEU, METEOR an...

Many machine translation (MT) evaluation metrics have been shown to correlate better with human judgment than BLEU. In principle, tuning on these metrics should yield better systems than tuning on BLEU. However, due to issues such as speed, requirements for linguistic resources, and optimization difficulty, they have not been widely adopted for tuning. This paper presents PORT 1 , a new MT eval...

We study a problem with pairwise ranking optimization (PRO): that it tends to yield too short translations. We find that this is partially due to the inadequate smoothing in PRO’s BLEU+1, which boosts the precision component of BLEU but leaves the brevity penalty unchanged, thus destroying the balance between the two, compared to BLEU. It is also partially due to PRO optimizing for a sentence-l...