Zhenbiao Chen

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This paper describes a Japanese-to-Chinese spoken language translation (SLT) method based on simple expression and presents the experimental results. The method is aimed at developing a compact speech translation system, which is robust for spontaneous spoken language phenomena, including the recognition errors and different expression from various(More)
In this paper, instead of designing new features based on intuition, linguistic knowledge and domain, we learn some new and effective features using the deep auto-encoder (DAE) paradigm for phrase-based translation model. Using the unsupervised pre-trained deep belief net (DBN) to initialize DAE's parameters and using the input original phrase features as a(More)
In this paper we propose a phrase-based translation system. In the system, we use phrase translation model instead of word-based model. An improved method of computing phrase translation probability is studied. We translate numeral phrases first by using a standard templates depository. We develop a phrase-based decoder that employs a beam search algorithm.(More)
This paper presents a new approach that uses linguistic knowledge and pronunciation space for automatic detection of typical phone-level errors made by non-native speakers of mandarin. Firstly, linguistic knowledge of common learner mistakes is embedded in the calculation of log-posterior probability and the revised log-posterior probability (RLPP) is(More)
We present a phrase-based method to extract parallel fragments from the comparable corpora. We do this by introducing a force decoder based on the hierarchical phrase-based (HPB) translation model to detect the alignments in comparable sentence pairs. This method enables us to extract useful training data for statistical machine translation (SMT) system. We(More)