Translating Phrases in Neural Machine Translation

Phrases play an important role in natural language understanding and machine translation (Sag et al., 2002; Villavicencio et al., 2005). However, it is difficult to integrate them into current neural machine translation (NMT) which reads and generates sentences word by word. In this work, we propose a method to translate phrases in NMT by integrating a phrase memory storing target phrases from a phrase-based statistical machine translation (SMT) system into the encoder-decoder architecture of NMT. At each decoding step, the phrase memory is first re-written by the SMT model, which dynamically generates relevant target phrases with contextual information provided by the NMT model. Then the proposed model reads the phrase memory to make probability estimations for all phrases in the phrase memory. If phrase generation is carried on, the NMT decoder selects an appropriate phrase from the memory to perform phrase translation and updates its decoding state by consuming the words in the selected phrase. Otherwise, the NMT decoder generates a word from the vocabulary as the general NMT decoder does. Experiment results on the Chinese to English translation show that the proposed model achieves significant improvements over the baseline on various test sets.Comment: Accepted by EMNLP 201

Label free colorimetric sensing of thiocyanate based on inducing aggregation of Tween 20-stabilized gold nanoparticles

Based on inducing the aggregation of gold nanoparticles (AuNPs), a simple colorimetric method with high sensitivity and selectivity was developed for the sensing of thiocyanate (SCN-) in aqueous solutions. Citrate-capped AuNPs were prepared following a classic method and Tween 20 was subsequently added as a stabilizer. With the addition of SCN-, citrate ions on AuNPs surfaces were replaced due to the high affinity between SCN- and Au. As a result, Tween 20 molecules adsorbed on the AuNPs surfaces were separated and the AuNPs aggregated. The process was accompanied by a visible color change from red to blue within 5 min. The sensing of SCN- can therefore be easily achieved by a UV-vis spectrophotometer or even by the naked eye. The potential effects of relevant experimental conditions, including concentration of Tween 20, pH, incubation temperature and time, were evaluated to optimize the method. Under optimized conditions, this method yields excellent sensitivity (LOD = 0.2 mu M or 11.6 ppb) and selectivity toward SCN-. Our attempt may provide a cost-effective, rapid and simple solution to the inspection of SCN- ions in saliva and environmental aqueous samples