Articles

Empirical studies on corpora involve mak- ing measurements of several quantities for the purpose of comparing corpora, creat- ing language models or to make general- izations about specific linguistic phenom- ena in a language. Quantities such as av- erage word length are stable across sam- ple sizes and hence can …...

In this paper, we propose a new Bayesian model for fully unsupervised word seg- mentation and an efficient blocked Gibbs sampler combined with dynamic program- ming for inference. Our model is a nested hierarchical Pitman-Yor language model, where Pitman-Yor spelling model is em- bedded in the word model. We confirmed …...

Minimum Error Rate Training (MERT) and Minimum Bayes-Risk (MBR) decod- ing are used in most current state-of-the- art Statistical Machine Translation (SMT) systems. The algorithms were originally developed to work with N-best lists of translations, and recently extended to lat- tices that encode many more hypotheses than typical N-best lists. …...

A central problem in grounded language acqui- sition is learning the correspondences between a rich world state and a stream of text which refer- ences that world state. To deal with the high de- gree of ambiguity present in this setting, we present a generative model that simultaneously segments the …...

In this paper, we present a reinforce- ment learning approach for mapping nat- ural language instructions to sequences of executable actions. We assume access to a reward function that defines the qual- ity of the executed actions. During train- ing, the learner repeatedly constructs ac- tion sequences for a set …...

We investigate the task of unsupervised constituency parsing from bilingual par- allel corpora. Our goal is to use bilin- gual cues to learn improved parsing mod- els for each language and to evaluate these models on held-out monolingual test data. We formulate a generative Bayesian model which seeks to explain …...

Freer-word-order languages such as Ger- man exhibit linguistic phenomena that present unique challenges to traditional CFG parsing. Such phenomena produce discontinuous constituents, which are not naturally modelled by projective phrase structure trees. In this paper, we exam- ine topological field parsing, a shallow form of parsing which identifies the ma- …...

This paper proposes an approach to en- hance dependency parsing in a language by using a translated treebank from an- other language. A simple statistical ma- chine translation method, word-by-word decoding, where not a parallel corpus but a bilingual lexicon is necessary, is adopted for the treebank translation. Using an …...

We address the issue of using heteroge- neous treebanks for parsing by breaking it down into two sub-problems, convert- ing grammar formalisms of the treebanks to the same one, and parsing on these homogeneous treebanks. First we pro- pose to employ an iteratively trained tar- get grammar parser to perform …...

We describe a semantic role labeling system that makes primary use of CCG-based fea- tures. Most previously developed systems are CFG-based and make extensive use of a treepath feature, which suffers from data spar- sity due to its use of explicit tree configura- tions. CCG affords ways to augment treepath- …...

The task of Semantic Role Labeling (SRL) is often divided into two sub-tasks: verb argument identification, and argu- ment classification. Current SRL algo- rithms show lower results on the identifi- cation sub-task. Moreover, most SRL al- gorithms are supervised, relying on large amounts of manually created data. In this paper …...

A number of studies have presented machine-learning approaches to semantic role labeling with availability of corpora such as FrameNet and PropBank. These corpora define the semantic roles of predi- cates for each frame independently. Thus, it is crucial for the machine-learning ap- proach to generalize semantic roles across different frames, …...

In this paper, we present a new learning scenario, heterogeneous transfer learn- ing, which improves learning performance when the data can be in different feature spaces and where no correspondence be- tween data instances in these spaces is pro- vided. In the past, we have classified Chi- nese text documents …...

The vast majority of work on word senses has relied on predefined sense invento- ries and an annotation schema where each word instance is tagged with the best fit- ting sense. This paper examines the case for a graded notion of word meaning in two experiments, one which uses WordNet …...

In this paper, we extend methods from Roark and Hollingshead (2008) for reducing the worst-case complexity of a context-free pars- ing pipeline via hard constraints derived from finite-state tagging pre-processing. Methods from our previous paper achieved quadratic worst-case complexity. We prove here that al- ternate methods for choosing constraints can …...

Automatically extracting social meaning and intention from spoken dialogue is an impor- tant task for dialogue systems and social com- puting. We describe a system for detecting elements of interactional style: whether a speaker is awkward, friendly, or flirtatious. We create and use a new spoken corpus of 991 4-minute …...

. Identifying collocations in a text (e.g., break record) and correctly translating them (battre record vs. *casser record) represent key issues in machine translation, notably because of their prevalence in language and their syntactic flexibility. This article describes a method for discovering translation equivalents for collocations from parallel corpora, aimed …...

Word boundary detection in variable noise-level environments by support vector machine (SVM) using Low-band Wavelet Energy (LWE) and Zero Crossing Rate (ZCR) features is proposed in this paper. The Wavelet Energy is derived based on Wavelet transformation; it can reduce the affection of noise in a speech signal. With the …...

. Research on bilingual lexicon extraction from comparable corpora leads to promising results using large corpora (hundreds of billions of words) using the direct alignment method. However, when using smaller corpora (hundreds of thousands of words), results obtained are slightly lower. We propose to introduce some anchor points on which …...

. In contrast with other NLP subtasks, there has been only few and limited evaluation campaigns for terminology acquisition. It is nevertheless important to assess the progress made, the quality and limitations of terminological tools. This paper argues that it is possible to define evaluation protocols for tasks as complex …...