Articles

We consider the evaluation problem in Natural Language Generation (NLG) and present results for evaluating several NLG systems with similar functionality, includ- ing a knowledge-based generator and sev- eral statistical systems. We compare eval- uation results for these systems by human domain experts, human non-experts, and several automatic evaluation metrics, …...

This paper discusses two problems that arise in the Generation of Referring Expressions: (a) numeric-valued attributes, such as size or location; (b) perspective-taking in reference. Both problems, it is argued, can be resolved if some structure is imposed on the available knowledge prior to content determination. We describe a clustering …...

We present and compare two approaches to the task of summarizing evaluative ar- guments. The first is a sentence extraction- based approach while the second is a lan- guage generation-based approach. We evaluate these approaches in a user study and find that they quantitatively perform equally well. Qualitatively, however, we …...

We present a model for sentence com- pression that uses a discriminative large- margin learning framework coupled with a novel feature set defined on compressed bigrams as well as deep syntactic repre- sentations provided by auxiliary depen- dency and phrase-structure parsers. The parsers are trained out-of-domain and con- tain a …...

Given the growing complexity of tasks that spoken dialogue systems are trying to handle, Reinforcement Learning (RL) has been increasingly used as a way of au- tomatically learning the best policy for a system to make. While most work has focused on generating better policies for a dialogue manager, very …...

Detection of discourse structure is crucial in many text-based applications. This pa- per presents an original framework for de- scribing textual parallelism which allows us to generalize various discourse phe- nomena and to propose a unique method to recognize them. With this prospect, we discuss several methods in order to …...

In this paper, we investigate the prob- lem of automatically predicting segment boundaries in spoken multiparty dialogue. We extend prior work in two ways. We first apply approaches that have been pro- posed for predicting top-level topic shifts to the problem of identifying subtopic boundaries. We then explore the impact …...

We present an adaptive technique that en- ables users to produce a high quality dic- tionary parsed into its lexicographic com- ponents (headwords, pronunciations, parts of speech, translations, etc.) using an extremely small amount of user provided training data. We use transformation- based learning (TBL) as a postprocessor at two …...

We argue that the machine translation community is overly reliant on the Bleu machine translation evaluation metric. We show that an improved Bleu score is nei- ther necessary nor sufficient for achieving an actual improvement in translation qual- ity, and give two significant counterex- amples to Bleu’s correlation with human …...

Most state-of-the-art evaluation measures for machine translation assign high costs to movements of word blocks. In many cases though such movements still result in correct or almost correct sentences. In this paper, we will present a new eval- uation measure which explicitly models block reordering as an edit operation. Our …...

Web text has been successfully used as training data for many NLP applications. While most previous work accesses web text through search engine hit counts, we created a Web Corpus by downloading web pages to create a topic-diverse collec- tion of 10 billion words of English. We show that for …...

We propose a method for compiling bi- lingual terminologies of multi-word terms (MWTs) for given translation pairs of seed terms. Traditional methods for bi- lingual terminology compilation exploit parallel texts, while the more recent ones have focused on comparable corpora. We use bilingual corpora collected from the web and tailor …...

In this paper, we present an automated, quantitative, knowledge-poor method to evaluate the randomness of a collection of documents (corpus), with respect to a number of biased partitions. The method is based on the comparison of the word frequency distribution of the target corpus to word frequency distributions from cor- …...

Opinion mining is a recent subdiscipline of computational linguistics which is con- cerned not with the topic a document is about, but with the opinion it expresses. To aid the extraction of opinions from text, recent work has tackled the issue of determining the orientation of “subjec- tive” terms contained …...

We propose models for semantic orienta- tions of phrases as well as classification methods based on the models. Although each phrase consists of multiple words, the semantic orientation of the phrase is not a mere sum of the orientations of the com- ponent words. Some words can invert the orientation. …...

This paper proposes a method for deal- ing with repairs in action control dialogue to resolve participants’ misunderstanding. The proposed method identifies the re- pair target based on common grounding rather than surface expressions. We extend Traum’s grounding act model by introduc- ing degree of groundedness, and partial and mid-discourse …...

We present results on addressee identifica- tion in four-participants face-to-face meet- ings using Bayesian Network and Naive Bayes classifiers. First, we investigate how well the addressee of a dialogue act can be predicted based on gaze, ut- terance and conversational context fea- tures. Then, we explore whether informa- tion about …...

Aligning sentences belonging to compa- rable monolingual corpora has been sug- gested as a first step towards training text rewriting algorithms, for tasks such as summarization or paraphrasing. We present here a new monolingual sen- tence alignment algorithm, combining a sentence-based TF*IDF score, turned into a probability distribution using logistic …...

Many of the tasks required for semantic tagging of phrases and texts rely on a list of words annotated with some semantic features. We present a method for ex- tracting sentiment-bearing adjectives from WordNet using the Sentiment Tag Extrac- tion Program (STEP). We did 58 STEP runs on unique non-intersecting …...

We describe a word alignment platform which ensures text pre-processing (to- kenization, POS-tagging, lemmatization, chunking, sentence alignment) as re- quired by an accurate word alignment. The platform combines two different methods, producing distinct alignments. The basic word aligners are described in some details and are individually evalu- ated. The union …...