Articles

This work is concerned with the space of alignments searched by word alignment systems. We focus on situations where word re-ordering is limited by syntax. We present two new alignment spaces that limit an ITG according to a given depen- dency parse. We provide D-ITG grammars to search these spaces …...

In this paper a novel solution to auto- matic and unsupervised word sense induc- tion (WSI) is introduced. It represents an instantiation of the ‘one sense per colloca- tion’ observation (Gale et al., 1992). Like most existing approaches it utilizes clus- tering of word co-occurrences. This ap- proach differs from …...

The degree of dominance of a sense of a word is the proportion of occurrences of that sense in text. We propose four new methods to accurately determine word sense dominance using raw text and a pub- lished thesaurus. Unlike the McCarthy et al. (2004) system, these methods can be …...

Probabilistic Latent Semantic Analysis (PLSA) models have been shown to pro- vide a better model for capturing poly- semy and synonymy than Latent Seman- tic Analysis (LSA). However, the param- eters of a PLSA model are trained using the Expectation Maximization (EM) algo- rithm, and as a result, the trained …...

In this paper, we address the problem of reducing the unpredictability of user- initiated dialogue contributions in human- computer interaction without explicitly re- stricting the user’s interactive possibili- ties. We demonstrate that it is possible to identify conditions under which particular classes of user-initiated contributions will occur and discuss consequences …...

In recent years tree kernels have been pro- posed for the automatic learning of natural language applications. Unfortunately, they show (a) an inherent super linear complex- ity and (b) a lower accuracy than tradi- tional attribute/value methods. In this paper, we show that tree kernels are very helpful in the …...

This paper presents results from the first statistical dependency parser for Turkish. Turkish is a free-constituent order lan- guage with complex agglutinative inflec- tional and derivational morphology and presents interesting challenges for statisti- cal parsing, as in general, dependency re- lations are between “portions” of words – called inflectional groups. …...

In this paper we extend the maximum spanning tree (MST) dependency parsing framework of McDonald et al. (2005c) to incorporate higher-order feature rep- resentations and allow dependency struc- tures with multiple parents per word. We show that those extensions can make the MST framework computationally in- tractable, but that the …...

We investigate a series of graph-theoretic constraints on non-projective dependency parsing and their effect on expressivity, i.e. whether they allow naturally occurring syntactic constructions to be adequately represented, and efficiency, i.e. whether they reduce the search space for the parser. In particular, we define a new measure for the degree …...

To tackle the problem of presenting a large number of options in spoken dia- logue systems, we identify compelling op- tions based on a model of user preferences, and present tradeoffs between alternative options explicitly. Multiple attractive op- tions are structured such that the user can gradually refine her request …...

In this paper, we explore statistical lan- guage modelling for a speech-enabled MP3 player application by generating a corpus from the interpretation grammar written for the application with the Gram- matical Framework (GF) (Ranta, 2004). We create a statistical language model (SLM) directly from our interpretation grammar and compare recognition …...

We present an implemented machine learning system for the automatic detec- tion of nonreferential it in spoken dialog. The system builds on shallow features ex- tracted from dialog transcripts. Our exper- iments indicate a level of performance that makes the system usable as a preprocess- ing filter for a coreference …...

We propose a backoff model for phrase- based machine translation that translates unseen word forms in foreign-language text by hierarchical morphological ab- stractions at the word and the phrase level. The model is evaluated on the Europarl corpus for German-English and Finnish- English translation and shows improve- ments over state-of-the-art …...

In this paper we study a set of prob- lems that are of considerable importance to Statistical Machine Translation (SMT) but which have not been addressed satis- factorily by the SMT research community. Over the last decade, a variety of SMT algorithms have been built and empiri- cally tested whereas …...

We present a weakly supervised approach to automatic Ontology Population from text and compare it with other two unsu- pervised approaches. In our experiments we populate a part of our ontology of Named Entities. We considered two high level categories - geographical locations and person names and ten sub-classes for …...

We present a new method for detecting and disambiguating named entities in open do- main text. A disambiguation SVM kernel is trained to exploit the high coverage and rich structure of the knowledge encoded in an online encyclopedia. The resulting model significantly outperforms a less in- formed baseline. 1...

This paper describes a novel method for computing a consensus translation from the outputs of multiple machine trans- lation (MT) systems. The outputs are combined and a possibly new transla- tion hypothesis can be generated. Simi- larly to the well-established ROVER ap- proach of (Fiscus, 1997) for combining speech recognition …...

We propose an approach for extracting re- lations between entities from biomedical literature based solely on shallow linguis- tic information. We use a combination of kernel functions to integrate two different information sources: (i) the whole sen- tence where the relation appears, and (ii) the local contexts around the interacting …...

Previous work shows that the process of parallel text exploitation to extract transfer mappings between language pairs raises the capability of language translation. However, while this process can be fully automated, one thorny problem called “divergence” causes indisposed mapping extraction. Therefore, this paper discuss the issues of parallel text exploitation, …...

This paper aims to further probe into the problems of ambiguities in automatic identification of determinative-measure compounds (DMs) in Chinese. It is known that Chinese DMs are identifiable by regular expression rules. However, rule matching only partially solve structural and lexical ambiguities. In this paper, a deep analyses based on …...