Articles

Recently, shallow parsing has been applied to various information processing systems, such as information retrieval, information extraction, question answering, and automatic document summarization. A shallow parser is suitable for online applications, because it is much more efficient and less demanding than a full parser. In this research, we formulate shallow …...

Recognizing transliteration names is challenging due to their flexible formulation and coverage of a lexicon. This paper employs the Web as a huge-scale corpus. The patterns extracted from the Web are considered as a live dictionary to correct speech recognition errors. In our approach, the plausible character strings recognized by …...

. In this paper, we proposed a weighted discrete K-nearest neighbor (weighted D-KNN) classification algorithm for detecting and evaluating emotion from Mandarin speech. In the experiments of the emotion recognition, Mandarin emotional speech database used contains five basic emotions, including anger, happiness, sadness, boredom and neutral, and the extracted acoustic …...

Polarity inversion based speech watermarking scheme hide data in speech by modification of the speech polarity. This paper build a statistical model of the polarity detection problem, based on this model, the original polarity detection scheme and the optimal detection scheme are analyzed and compared. The theoretical analysis results are …...

. TF*IDF-based methods, as they are easily to implement, are widely accepted in information retrieval industry. It is interesting to investigate a feasible and practical technique to improve the retrieval performance of these conventional IR methods. In this paper, we are going to introduce a good alternative approach that uses …...

In this paper, we develop an automatic metadata creation system using the information extraction technology for the Semantic Web. The information extraction system consists of preparation part that takes written text as the input and produces the POS tags for the words in the sentences. Then we employ finite state …...

Recently, we have proposed several effective Web-based term translation extraction methods exploring Web resources to deal with translation of Web query terms. However, many unknown proper names in Web queries are still difficult to be translated by using our previous Web-based term translation extraction methods. Therefore, in this paper we …...

This paper presents a new speech enhancement approach originated from factor analysis (FA) framework. FA is a data analysis model where the relevant common factors can be extracted from observations. A factor loading matrix is found and a resulting model error is introduced for each observation. Interestingly, FA is a …...

. We explore the use of a partially annotated corpus to build a depen- dency parser for Japanese. We examine two types of partially annotated corpora. It is found that a parser trained with a corpus that does not have any grammatical tags for words can demonstrate an accuracy of …...

. We build a class-based selection preference sub-model to in- corporate external semantic knowledge from two Chinese electronic se- mantic dictionaries. This sub-model is combined with modifier-head gen- eration sub-model. After being optimized on the held out data by the EM algorithm, our improved parser achieves 79.4% (F1 measure), as …...

We explore the benefit that users in sev- eral application areas can experience from a “tab-complete” editing assistance func- tion. We develop an evaluation metric and adapt N-gram language models to the problem of predicting the subsequent words, given an initial text fragment. Us- ing an instance-based method as base- …...

Humor is one of the most interesting and puzzling aspects of human behavior. De- spite the attention it has received in fields such as philosophy, linguistics, and psy- chology, there have been only few at- tempts to create computational models for humor recognition or generation. In this paper, we bring …...

We present a new word-alignment ap- proach that learns errors made by ex- isting word alignment systems and cor- rects them. By adapting transformation- based learning to the problem of word alignment, we project new alignment links from already existing links, using features such as POS tags. We show that …...

This paper describes a system for the CoNLL-2005 Shared Task on Semantic Role Labeling. We trained two parsers with the training corpus in which the se- mantic argument information is attached to the constituent labels, we then used the resulting parse trees as the input of the pipelined SRL system. …...

In this paper, we propose a method that exploits full parsing information by repre- senting it as features of argument classifi- cation models and as constraints in integer linear learning programs. In addition, to take advantage of SVM-based and Maxi- mum Entropy-based argument classifica- tion models, we incorporate their scoring …...

A striking feature of human syntactic pro- cessing is that it is context-dependent, that is, it seems to take into account seman- tic information from the discourse con- text and world knowledge. In this paper, we attempt to use this insight to bridge the gap between SRL results from gold …...

In this paper we introduce a semantic role labeling system constructed on top of the full syntactic analysis of text. The la- beling problem is modeled using a rich set of lexical, syntactic, and semantic at- tributes and learned using one-versus-all AdaBoost classifiers. Our results indicate that even a simple …...

This paper describes a semantic role la- beling system that uses features derived from different syntactic views, and com- bines them within a phrase-based chunk- ing paradigm. For an input sentence, syn- tactic constituent structure parses are gen- erated by a Charniak parser and a Collins parser. Semantic role labels …...

Our system for semantic role labeling is multi-stage in nature, being based on tree pruning techniques, statistical methods for lexicalised feature encoding, and a C4.5 decision tree classifier. We use both shal- low and deep syntactic information from automatically generated chunks and parse trees, and develop a model for learning …...

We describe a system for the CoNLL- 2005 shared task of Semantic Role Label- ing. The system implements a two-layer architecture to first identify the arguments and then to label them for each predicate. The components are implemented as SVM classifiers using libSVM. Features were adapted and tuned for the …...