Embedding Web-based Statistical Translation Models in Cross-Language Information Retrieval

Although more and more language pairs are covered by machine translation services, there are still many pairs that lack translation resources. Cross-language information retrieval (CLIR) is an application which needs translation functionality of a relatively low level of sophistication since current models for information retrieval (IR) are still based on a bag-of-words. The Web provides a vast resource for the automatic construction of parallel corpora which can be used to train statistical translation models automatically. The resulting translation models can be embedded in several ways in a retrieval model. In this paper, we will investigate the problem of automatically mining parallel texts from the Web and different ways of integrating the translation models within the retrieval process. Our experiments on standard test collections for CLIR show that the Web-based translation models can surpass commercial MT systems in CLIR tasks. These results open the perspective of constructing a fully automatic query translation device for CLIR at a very low cost.Comment: 37 page

Are You Finding the Right Person? A Name Translation System Towards Web 2.0

In a multilingual world, information available in global information systems is increasing rapidly. Searching for proper names in foreign language becomes an important task in multilingual search and knowledge discovery. However, these names are the most difficult to handle because they are often unknown words that cannot be found in a translation dictionary and even human experts cannot handle the variation generated during translation. Furthermore, existing research on name translation have focused on translation algorithms. However, user experience during name translation and name search are often ignored. With the Web technology moving towards Web 2.0, creating a platform that allow easier distributed collaboration and information sharing, we seek methods to incorporate Web 2.0 technologies into a name translation system. In this research, we review challenges in name translation and propose an interactive name translation and search system: NameTran. This system takes English names and translates them into Chinese using a combined hybrid Hidden Markov Model-based (HMM-based) transliteration approach and a web mining approach. Evaluation results showed that web mining consistently boosted the performance of a pure HMM approach. Our system achieved top-1 accuracy of 0.64 and top-8 accuracy of 0.96. To cope with changing popularity and variation in name translations, we demonstrated the feasibility of allowing users to rank translations and the new ranking serves as feedback to the original trained HMM model. We believe that such user input will significantly improve system usability

Learning Spatial-Semantic Context with Fully Convolutional Recurrent Network for Online Handwritten Chinese Text Recognition

Online handwritten Chinese text recognition (OHCTR) is a challenging problem as it involves a large-scale character set, ambiguous segmentation, and variable-length input sequences. In this paper, we exploit the outstanding capability of path signature to translate online pen-tip trajectories into informative signature feature maps using a sliding window-based method, successfully capturing the analytic and geometric properties of pen strokes with strong local invariance and robustness. A multi-spatial-context fully convolutional recurrent network (MCFCRN) is proposed to exploit the multiple spatial contexts from the signature feature maps and generate a prediction sequence while completely avoiding the difficult segmentation problem. Furthermore, an implicit language model is developed to make predictions based on semantic context within a predicting feature sequence, providing a new perspective for incorporating lexicon constraints and prior knowledge about a certain language in the recognition procedure. Experiments on two standard benchmarks, Dataset-CASIA and Dataset-ICDAR, yielded outstanding results, with correct rates of 97.10% and 97.15%, respectively, which are significantly better than the best result reported thus far in the literature.Comment: 14 pages, 9 figure

Akchessima: Latin Type Design for Digital Chinese (Seal Script) Typefaces

As multi-language text layout and Chinese/Japanese/Korean typefaces has become an important topic in modern day typography, the visual match-making between Latin and Chinese writing is a very important issue in type design. For this thesis project, Latin letters are designed based on a Chinese seal script style typeface, in seek of a design principle of matching Latin letter forms for Chinese calligraphic styles, originating from different writing tools and traditions. There is not one universal principle that would apply on all different Chinese typeface styles. However, based on research of writing habits and technology, multiple methods have been developed in this thesis, which could be used while processing any type design projects

Taijiquan the 'Taiji World' way: Towards a cosmopolitan vision of ecology.

In this article, we present a case study analysis of data gathered on the practice of the art of Taijiquan (Tai Chi Chuan) in one UK context. Our interest in looking at this physical culture was in exploring if/how physical cultures of shared embodied experience and practice may help “sow the seeds of environmental awareness”. In so doing, we illustrate certain affinities between this interpretation of the art and Beck’s idea of a “cosmopolitan vision of ecology”. We present an analysis of documentary and interview data of one English Taijiquan organisation and how it currently promotes the idea of interconnectedness, wellbeing and an alternative meta-narrative for living through the practice of Taijiquan. We conclude that, while further research is needed, there is evidence that a cosmopolitan vision for ecology is emerging in physical cultures such as Taijiquan