首页|New Machine Translation Findings from Kunming University Described (Dra: Dynamic Routing Attention for Neural Machine Translation With Low-resource Languages)
New Machine Translation Findings from Kunming University Described (Dra: Dynamic Routing Attention for Neural Machine Translation With Low-resource Languages)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-Current study results on Machine Trans lation have been published. According to news reporting out of Kunming, People's Republic of China, by NewsRx editors, research stated, "In recent years, the ut ilization of deep models has significantly enhanced the performance of neural ma chine translation (NMT). Nevertheless, the uneven distribution of data leads to critical challenges." Financial supporters for this research include National Natural Science Foundati on of China (NSFC), Yunnan Provincial Science and Technology Major Special Proje ct, Yunnan Provincial Basic Research Programme Project. Our news journalists obtained a quote from the research from Kunming University, "Specifically, lowfrequency words severely affect translation performance. Thi s is especially in low-resource language translation, where the training of low- frequency words is inadequate. To address this issue, we use syntactic and word frequency information to enhance the performance of encoding representations of input sequence. we propose a simple approach called Dynamic Routing Attention (D RA). When processing different words, DRA dynamically adjusts the Self-attention weight based on word frequency and source syntactic, which enables the encoder Self-attention to focus on the surrounding words and the words with syntactic as sociations rather than the current word solely. Consequently, our method improve s the representation capability of the encoder in processing sentences containin g low-frequency words. Using Transformer RPR model as a baseline model, we demon strate the effectiveness of our method with the experiments on machine translati on tasks of WMT14 English-German, IWLST14 English-German, IWLST14 English-Vietna mese, and TED talk Thai-Chinese."
KunmingPeople's Republic of ChinaAsi aEmerging TechnologiesMachine LearningMachine TranslationKunming Univers ity
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