Articles

This paper presents a formal analysis for a large class of words called alternative markers, which includes other(than), such(as), and besides. These words appear frequently enough in dialog to warrant serious attention, yet present natural language search engines perform poorly on queries containing them. show that the performance of a …...

While paraphrasing is critical both for interpretation and generation of natu- ral language, current systems use man- ual or semi-automatic methods to col- lect paraphrases. We present an un- supervised learning algorithm for iden- tification of paraphrases from a cor- pus of multiple English translations of the same source text. …...

In this paper we argue that comparative evaluation in anaphora resolution has to be performed using the same pre-processing tools and on the same set of data. The paper proposes an evaluation environment for comparing anaphora resolution algorithms which is illustrated by presenting the results of the comparative evaluation of …...

The theoretical study of the range concatenation grammar [RCG] formal- ism has revealed many attractive prop- erties which may be used in NLP. In particular, range concatenation lan- guages [RCL] can be parsed in poly- nomial time and many classical gram- matical formalisms can be translated into equivalent RCGs without …...

In this paper, we compare the rela- tive effects of segment order, segmen- tation and segment contiguity on the retrieval performance of a translation memory system. We take a selec- tion of both bag-of-words and segment order-sensitive string comparison meth- ods, and run each over both character- and word-segmented data, …...

In this paper, we propose adding long-term grammatical information in a Whole Sentence Maximun Entropy Language Model (WSME) in order to improve the performance of the model. The grammatical information was added to the WSME model as fea- tures and were obtained from a Stochas- tic Context-Free grammar. Finally, ex- …...

This paper addresses recent progress in speaker-independent, large vocabulary, continuous speech recognition, which has opened up a wide range of near and mid-term applications. One rapidly ex- panding application area is the process- ing of broadcast audio for information access. At LIMSI, broadcast news tran- scription systems have been developed …...

The amount of readily available on-line text has reached hundreds of billions of words and continues to grow. Yet for most core natural language tasks, algorithms continue to be optimized, tested and compared after training on corpora consisting of only one million words or less. In this paper, we evaluate …...

In this paper, a new language model, the Multi-Class Composite N-gram, is pro- posed to avoid a data sparseness prob- lem for spoken language in that it is difficult to collect training data. The Multi-Class Composite N-gram main- tains an accurate word prediction ca- pability and reliability for sparse data …...

Many machine learning methods have recently been applied to natural lan- guage processing tasks. Among them, the Winnow algorithm has been ar- gued to be particularly suitable for NLP problems, due to its robustness to ir- relevant features. However in theory, Winnow may not converge for non- separable data. To …...

We present a syntax-based statistical translation model. Our model trans- forms a source-language parse tree into a target-language string by apply- ing stochastic operations at each node. These operations capture linguistic dif- ferences such as word order and case marking. Model parameters are esti- mated in polynomial time using an …...

Multi-processor systems are becom- ing more commonplace and afford- able. Based on analyses of ac- tual parsings, we argue that to ex- ploit the capabilities of such ma- chines, unification-based grammar parsers should distribute work at the level of individual unification oper- ations. We present a generic ap- proach to …...

We describe a set of supervised ma- chine learning experiments centering on the construction of statistical mod- els of WH-questions. These models, which are built from shallow linguis- tic features of questions, are employed to predict target variables which repre- sent a user’s informational goals. We report on different aspects …...

The standard pipeline approach to se- mantic processing, in which sentences are morphologically and syntactically resolved to a single tree before they are interpreted, is a poor fit for ap- plications such as natural language in- terfaces. This is because the environ- ment information, in the form of the ob- …...

This paper describes the application of the PARADISE evaluation framework to the corpus of 662 human-computer dialogues collected in the June 2000 Darpa Communicator data collection. We describe results based on the stan- dard logfile metrics as well as results based on additional qualitative metrics derived using the DATE dialogue …...

In a headed tree, each terminal word can be uniquely labeled with a gov- erning word and grammatical relation. This labeling is a summary of a syn- tactic analysis which eliminates detail, reflects aspects of semantics, and for some grammatical relations (such as subject of finite verb) is nearly un- …...

We propose a statistical method that finds the maximum-probability seg- mentation of a given text. This method does not require training data because it estimates probabilities from the given text. Therefore, it can be applied to any text in any domain. An experi- ment showed that the method is more …...

The STOP system, which generates personalised smoking-cessation letters, was evaluated by a randomised con- trolled clinical trial. We believe this is the largest and perhaps most rigorous task effectiveness evaluation ever per- formed on an NLG system. The de- tailed results of the clinical trial have been presented elsewhere, in …...

Techniques for automatically training modules of a natural language gener- ator have recently been proposed, but a fundamental concern is whether the quality of utterances produced with trainable components can compete with hand-crafted template-based or rule- based approaches. In this paper We ex- perimentally evaluate a trainable sen- tence planner …...

This paper presents a method that as- sists in maintaining a rule-based named-entity recognition and classifi- cation system. The underlying idea is to use a separate system, constructed with the use of machine learning, to monitor the performance of the rule-based sys- tem. The training data for the second system …...