Articles

Recent research has shown that language and the socio-cognitive phenomena asso- ciated with it can be aptly modeled and visualized through networks of linguistic entities. However, most of the existing works on linguistic networks focus only on the local properties of the networks. This study is an attempt to analyze …...

In this paper, we explore unsupervised techniques for the task of automatic short answer grading. We compare a number of knowledge-based and corpus-based mea- sures of text similarity, evaluate the effect of domain and size on the corpus-based measures, and also introduce a novel tech- nique to improve the performance …...

Lexical-semantic resources are used ex- tensively for applied semantic inference, yet a clear quantitative picture of their current utility and limitations is largely missing. We propose system- and application-independent evaluation and analysis methodologies for resources’ per- formance, and systematically apply them to seven prominent resources. Our find- ings identify the …...

We address the task of automatically pre- dicting if summarization system perfor- mance will be good or bad based on fea- tures derived directly from either single- or multi-document inputs. Our labelled cor- pus for the task is composed of data from large scale evaluations completed over the span of …...

We introduce a word segmentation ap- proach to languages where word bound- aries are not orthographically marked, with application to Phrase-Based Statis- tical Machine Translation (PB-SMT). In- stead of using manually segmented mono- lingual domain-specific corpora to train segmenters, we make use of bilingual cor- pora and statistical word alignment …...

We present a unified view of many trans- lation algorithms that synthesizes work on deductive parsing, semiring parsing, and efficient approximate search algorithms. This gives rise to clean analyses and com- pact descriptions that can serve as the ba- sis for modular implementations. We illus- trate this with several examples, …...

We present the results of a large-scale, end-to-end human evaluation of various sentiment summarization models. The evaluation shows that users have a strong preference for summarizers that model sentiment over non-sentiment baselines, but have no broad overall preference be- tween any of the sentiment-based models. However, an analysis of the …...

The quality of the part-of-speech (PoS) annotation in a corpus is crucial for the development of PoS taggers. In this pa- per, we experiment with three complemen- tary methods for automatically detecting errors in the PoS annotation for the Ice- landic Frequency Dictionary corpus. The first two methods are language …...

We use a machine learner trained on a combination of acoustic and contextual features to predict the accuracy of incom- ing n-best automatic speech recognition (ASR) hypotheses to a spoken dialogue system (SDS). Our novel approach is to use a simple statistical User Simulation (US) for this task, which measures …...

We present a language-pair independent terminology extraction module that is based on a sub-sentential alignment sys- tem that links linguistically motivated phrases in parallel texts. Statistical filters are applied on the bilingual list of candi- date terms that is extracted from the align- ment output. We compare the performance of …...

Handling terminology is an important matter in a translation workflow. However, current Machine Translation (MT) sys- tems do not yet propose anything proactive upon tools which assist in managing termi- nological databases. In this work, we in- vestigate several enhancements to analog- ical learning and test our implementation on translating …...

An open problem in dependency parsing is the accurate and efficient treatment of non-projective structures. We propose to attack this problem using chart-parsing algorithms developed for mildly context- sensitive grammar formalisms. In this pa- per, we provide two key tools for this ap- proach. First, we show how to reduce …...

In this paper, we present a novel approach to integrate speech recognition and rule- based machine translation by lattice pars- ing. The presented approach is hybrid in two senses. First, it combines struc- tural and statistical methods for language modeling task. Second, it employs a chart parser which utilizes manually …...

We propose a novel algorithm for extract- ing dependencies from the derivations of a large fragment of CCG. Unlike earlier proposals, our dependency structures are always tree-shaped. We then use these de- pendency trees to compare the strong gen- erative capacities of CCG and TAG and obtain surprising results: Both …...

We show how global constraints such as transitiv- ity can be treated intensionally in a Zero-One Inte- ger Linear Programming (ILP) framework which is geared to find the optimal and coherent partition of coreference sets given a number of candidate pairs and their weights delivered by a pairwise classifier (used …...

One way to construct semantic represen- tations in a robust manner is to enhance shallow language processors with seman- tic components. Here, we provide a model theory for a semantic formalism that is de- signed for this, namely Robust Minimal Recursion Semantics (RMRS). We show that RMRS supports a notion …...

We present a Hebrew to English transliter- ation method in the context of a machine translation system. Our method uses ma- chine learning to determine which terms are to be transliterated rather than trans- lated. The training corpus for this purpose includes only positive examples, acquired semi-automatically. Our classifier reduces …...

In this paper we compare and contrast two approaches to Machine Translation (MT): the CMU-UKA Syntax Augmented Machine Translation system (SAMT) and UPC-TALP N-gram-based Statistical Ma- chine Translation (SMT). SAMT is a hier- archical syntax-driven translation system underlain by a phrase-based model and a target part parse tree. In N-gram-based …...

The present paper is concerned with sta- tistical parsing of constituent structures in German. The paper presents four ex- periments that aim at improving parsing performance of coordinate structure: 1) reranking the n-best parses of a PCFG parser, 2) enriching the input to a PCFG parser by gold scopes for …...

We describe a method for creating a non- English subjectivity lexicon based on an English lexicon, an online translation ser- vice and a general purpose thesaurus: Wordnet. We use a PageRank-like algo- rithm to bootstrap from the translation of the English lexicon and rank the words in the thesaurus by …...