Memory-augmented Neural Machine Translation

Neural machine translation (NMT) has achieved notable success in recent times, however it is also widely recognized that this approach has limitations with handling infrequent words and word pairs. This paper presents a novel memory-augmented NMT (M-NMT) architecture, which stores knowledge about how words (usually infrequently encountered ones) should be translated in a memory and then utilizes them to assist the neural model. We use this memory mechanism to combine the knowledge learned from a conventional statistical machine translation system and the rules learned by an NMT system, and also propose a solution for out-of-vocabulary (OOV) words based on this framework. Our experiments on two Chinese-English translation tasks demonstrated that the M-NMT architecture outperformed the NMT baseline by $9.0$ and $2.7$ BLEU points on the two tasks, respectively. Additionally, we found this architecture resulted in a much more effective OOV treatment compared to competitive methods

Flexible and Creative Chinese Poetry Generation Using Neural Memory

It has been shown that Chinese poems can be successfully generated by sequence-to-sequence neural models, particularly with the attention mechanism. A potential problem of this approach, however, is that neural models can only learn abstract rules, while poem generation is a highly creative process that involves not only rules but also innovations for which pure statistical models are not appropriate in principle. This work proposes a memory-augmented neural model for Chinese poem generation, where the neural model and the augmented memory work together to balance the requirements of linguistic accordance and aesthetic innovation, leading to innovative generations that are still rule-compliant. In addition, it is found that the memory mechanism provides interesting flexibility that can be used to generate poems with different styles

Density-dependent effect on reproductive behaviour of Lysmata amboinensis and L. boggessi (Decapoda: Caridea: Hippolytidae)

We compared the reproductive behaviours of two protandric simultaneous hermaphroditic species (Lysmata amboinensis and L. boggessi) that belong to two groups of Lysmata shrimp with different morphology, geographical distribution, and density. Lysmata amboinensis occurs in tropical waters at low population densities, and L. boggessi is found in aggregation in sub-tropical and temperate areas. Reproductive behaviour of L. boggessi under two densities and L. amboinensis in different habitats were compared. Results show that L. amboinensis was much less active during mating than L. boggessi. Male shrimp of L. amboinensis did not display obvious pre-copulation behaviour. They also took significantly longer to transfer spermatophores and lay eggs after mating than L. boggessi shrimp did. For L. boggessi, moulting time of female shrimp, copulation time and the interval between moulting and mating were significantly shorter when three male shrimp were present than when only one male shrimp was present. Our study suggests that the reproductive behavioural differences in the two shrimp species are possibly the results of density-dependent effect