Total Articles: 38870

nan

Publication: TIPSTER (2008)

DOI: nan

Paper ID: 12702

Orthographic variance is a fundamental problem for many natural language process- ing applications. The Japanese language, in particular, contains many orthographic vari- ants for two main reasons: (1) transliterated words allow many possible spelling varia- tions, and (2) many characters in Japanese nouns can be omitted or substituted. Pre- vious …...

nan

Publication: TIPSTER (2008)

DOI: nan

Paper ID: 12703

Topic Detection and Tracking refers to au- tomatic techniques for locating topically re- lated materials in streams of data. As the core technology of it, story link detection is to determine whether two stories are about the same topic. To overcome the limitation of the story length and the topic …...

nan

Publication: TIPSTER (2008)

DOI: nan

Paper ID: 12704

This paper proposes a semi-supervised learn- ing method for relation extraction. Given a small amount of labeled data and a large amount of unlabeled data, it first bootstraps a moderate number of weighted support vectors via SVM through a co-training procedure with random feature projection and then applies a label …...

nan

Publication: TIPSTER (2008)

DOI: nan

Paper ID: 12705

This paper proposes a context-sensitive convo- lution tree kernel for pronoun resolution. It re- solves two critical problems in previous researches in two ways. First, given a parse tree and a pair of an anaphor and an antecedent candidate, it implements a dynamic-expansion scheme to automatically determine a proper tree …...

nan

Publication: TIPSTER (2008)

DOI: nan

Paper ID: 12706

We present a technique for refining a base- line segmentation and generating a plausible underlying morpheme segmentation by inte- grating hand-written rewrite rules into an ex- isting state-of-the-art unsupervised morpho- logical induction procedure. Performance on measures which consider surface-boundary accuracy and underlying morpheme consis- tency indicates this technique leads to …...

nan

Publication: TIPSTER (2008)

DOI: nan

Paper ID: 12707

This paper reports our empirical evaluation and comparison of several popular good- ness measures for unsupervised segmenta- tion of Chinese texts using Bakeoff-3 data sets with a unified framework. Assuming no prior knowledge about Chinese, this frame- work relies on a goodness measure to iden- tify word candidates from unlabeled …...

nan

Publication: TIPSTER (2008)

DOI: nan

Paper ID: 12708

In Modern Mongolian, a content word can be inflected when concatenated with suf- fixes. Identifying the original forms of content words is crucial for natural lan- guage processing and information retrieval. We propose a lemmatization method for Modern Mongolian and apply our method to indexing for information retrieval. We use …...

nan

Publication: TIPSTER (2008)

DOI: nan

Paper ID: 10000

AbstractIn this paper, we describe NineOneOne (9-1-1), a system designed to recognize and translate Spanish emergency calls for better dispatching. We analyze the research challenges in adapting speech translation technology to 9-1-1 domain. We report our initial research towards building the system and the results of our initial experiments....

nan

Publication: TIPSTER (2008)

DOI: nan

Paper ID: 10001

AbstractWe evaluate discriminative parse reranking and parser self-training on a new English test set using four versions of the Charniak parser and a variety of parser evaluation metrics. The new test set consists of 1,000 hand-corrected British National Corpus parse trees. We directly evaluate parser output using both the Parseval …...

nan

Publication: TIPSTER (2008)

DOI: nan

Paper ID: 10002

AbstractSpeaker identification and verification systems have a poor performance when model training is done in one language while the testing is done in another. This situation is not unusual in multilingual environments, where people should be able to access the system in any language he or she prefers in each …...

nan

Publication: TIPSTER (2008)

DOI: nan

Paper ID: 10003

AbstractIn this paper we briefly describe the BioSec multimodal biometric database and analyze its use in automatic text-dependent speaker recognition research. The paper is structured into four parts: a short introduction to the problem of text-dependent speaker recognition; a brief review of other existing databases, including monomodal text-dependent speaker recognition …...

nan

Publication: TIPSTER (2008)

DOI: nan

Paper ID: 10004

AbstractThis paper addresses a specific case of the task of lexical acquisition understood as the induction of information about the linguistic characteristics of lexical items on the basis of information gathered from their occurrences in texts. Most of the recent works in the area of lexical acquisition have used methods …...

nan

Publication: TIPSTER (2008)

DOI: nan

Paper ID: 10005

AbstractIn this paper, we reported experiments of unsupervised automatic acquisition of Italian and English verb subcategorization frames (SCFs) from general and domain corpora. The proposed technique operates on syntactically shallow-parsed corpora on the basis of a limited number of search heuristics not relying on any previous lexico-syntactic knowledge about SCFs. …...

nan

Publication: TIPSTER (2008)

DOI: nan

Paper ID: 10006

AbstractSemantic databases are a stable starting point in developing knowledge based systems. Since creating language resources demands many temporal, financial and human resources, a possible solution could be the import of a resource annotation from one language to another. This paper presents the creation of a semantic role database for …...

nan

Publication: TIPSTER (2008)

DOI: nan

Paper ID: 10007

AbstractCase frames are an important knowledge base for a variety of natural language processing (NLP) systems. For the practical use of these systems in the real world, wide-coverage case frames are required. In order to acquire such large-scale case frames, in this paper, we automatically compile case frames from a …...

nan

Publication: TIPSTER (2008)

DOI: nan

Paper ID: 10008

AbstractThis paper describes an accurate, extensible method for automatically classifying unknown foreign words that requires minimal monolingual resources and no bilingual training data (which is often difficult to obtain for an arbitrary language pair). We use a small set of phonologically-based transliteration rules to generate a potentially unlimited amount of …...

nan

Publication: TIPSTER (2008)

DOI: nan

Paper ID: 10009

AbstractWe present the main outcomes of the COREA project: a corpus annotated with coreferential relations and a coreference resolution system for Dutch. In the project we developed annotation guidelines for coreference resolution for Dutch and annotated a corpus of 135K tokens. We discuss these guidelines, the annotation tool, and the …...

nan

Publication: TIPSTER (2008)

DOI: nan

Paper ID: 10010

AbstractWe present the second version of the Penn Discourse Treebank, PDTB-2.0, describing its lexically-grounded annotations of discourse relations and their two abstract object arguments over the 1 million word Wall Street Journal corpus. We describe all aspects of the annotation, including (a) the argument structure of discourse relations, (b) the …...

nan

Publication: TIPSTER (2008)

DOI: nan

Paper ID: 10011

AbstractIn this paper we investigate the coverage of the two knowledge sources WordNet and Wikipedia for the task of bridging resolution. We report on an annotation experiment which yielded pairs of bridging anaphors and their antecedents in spoken multi-party dialog. Manual inspection of the two knowledge sources showed that, with …...

nan

Publication: TIPSTER (2008)

DOI: nan

Paper ID: 10012

AbstractArrau is a new corpus annotated for anaphoric relations, with information about agreement and explicit representation of multiple antecedents for ambiguous anaphoric expressions and discourse antecedents for expressions which refer to abstract entities such as events, actions and plans. The corpus contains texts from different genres: task-oriented dialogues from the …...