In this work, we introduce the TESLACELAB metric (Translation Evaluation of Sentences with Linear-programming-based Analysis – Character-level Evaluation for Languages with Ambiguous word Boundaries) for automatic machine translation evaluation. For languages such as Chinese where words usually have meaningful internal structure and word boundaries are often fuzzy, TESLA-CELAB acknowledges the advantage of character-level evaluation over word-level evaluation.
This book contains most of the papers presented at the Eco-Architecture 2010
conference, which was the third edition of the International Conference on
Harmonisation between Architecture and Nature. Previous editions were held in
the New Forest, UK (2006) and the Algarve, Portugal (2008) and demonstrated the
importance of a forum like this to discuss the characteristics and challenges of such
Eco-Architecture implies a new approach to the design process intended to
harmonise its products with nature.
Well into the swiftly approaching millennium, project management will continue to be a highly desired skill
in the midst of great change. Because rigid organizational boundaries and responsibilities have blurred and
new technologies are changing the ways of doing business, results must be delivered more quickly and
accurately than ever before. These circumstances call for people who can deal with ambiguity and time
pressures while simultaneously accomplishing project goals—in other words, people who display excellence
in project management....
Well into the swiftly approaching millennium, project management will continue to be a highly desired skill in the midst of great change. Because rigid organizational boundaries and responsibilities have blurred and new technologies are changing the ways of doing business, results must be delivered more quickly and accurately than ever before. These circumstances call for people who can deal with ambiguity and time pressures while simultaneously accomplishing project goals—in other words, people who display excellence in project management....
We study the challenges raised by Arabic verb and subject detection and reordering in Statistical Machine Translation (SMT). We show that post-verbal subject (VS) constructions are hard to translate because they have highly ambiguous reordering patterns when translated to English. In addition, implementing reordering is difﬁcult because the boundaries of VS constructions are hard to detect accurately, even with a state-of-the-art Arabic dependency parser.
In this paper, we present a hybrid method for word segmentation and POS tagging. The target languages are those in which word boundaries are ambiguous, such as Chinese and Japanese. In the method, word-based and character-based processing is combined, and word segmentation and POS tagging are conducted simultaneously. Experimental results on multiple corpora show that the integrated method has high accuracy.
For languages that have no explicit word boundary such as Thai, Chinese and Japanese, correcting words in text is harder than in English because of additional ambiguities in locating error words. The traditional method handles this by hypothesizing that every substrings in the input sentence could be error words and trying to correct all of them. In this paper, we propose the idea of reducing the scope of spelling correction by focusing only on dubious areas in the input sentence.
This paper proposes a method for incrementally understanding user utterances whose semantic boundaries are not known and responding in real time even before boundaries are determined. It is an integrated parsing and discourse processing method that updates the partial result of understanding word by word, enabling responses based on the partial result. This method incrementally finds plausible sequences of utterances that play crucial roles in the task execution of dialogues, and utilizes beam search to deal with the ambiguity of boundaries as well as syntactic and semantic ambiguities. ...
We propose a statistical dialogue analysis model to determine discourse structures as well as speech acts using maximum entropy model. The model can automatically acquire probabilistic discourse knowledge from a discourse tagged corpus to resolve ambiguities. We propose the idea of tagging discourse segment boundaries to represent the structural information of discourse. Using this representation we can effectively combine speech act analysis and discourse structure analysis in one framework.
Japanese dependency structure is usually represented by relationships between phrasal units called bunsetsus. One of the biggest problems with dependency structure analysis in spontaneous speech is that clause boundaries are ambiguous. This paper describes a method for detecting the boundaries of quotations and inserted clauses and that for improving the dependency accuracy by applying the detected boundaries to dependency structure analysis.