Articles

In the field of Intelligent User Interfaces, Spo- ken Dialogue Systems (SDSs) play a key role as speech represents a true intuitive means of human communication. Deriving informa- tion about its quality can help rendering SDSs more user-adaptive. Work on automatic esti- mation of subjective quality usually relies on statistical …...

To solve data sparsity problem, recently there has been a trend in discriminative methods of NLP to use representations of lexical items learned from unlabeled data as features. In this paper, we investigated the usage of word representations learned by neural language models, i.e. word embeddings. The direct us- age …...

A discourse typically involves numerous en- tities, but few are mentioned more than once. Distinguishing discourse entities that die out after just one mention (singletons) from those that lead longer lives (coreferent) would ben- efit NLP applications such as coreference res- olution, protagonist identification, topic mod- eling, and discourse coherence. …...

Large unsupervised latent variable models (LVMs) of text, such as Latent Dirichlet Al- location models or Hidden Markov Models (HMMs), are constructed using parallel train- ing algorithms on computational clusters. The memory required to hold LVM parameters forms a bottleneck in training more powerful models. In this paper, we show …...

Word sense disambiguation aims to identify which meaning of a word is present in a given usage. Gathering word sense annotations is a laborious and difficult task. Several methods have been proposed to gather sense annota- tions using large numbers of untrained anno- tators, with mixed results. We propose three …...

This paper discusses the extension of a sys- tem developed for automatic discovery of tree- bank annotation inconsistencies over an entire corpus to the particular case of evaluation of inter-annotator agreement. This system makes for a more informative IAA evaluation than other systems because it pinpoints the incon- sistencies and …...

Incorporating semantic structure into linguistics-free translation model is chal-a lenging, since semantic structures are closely tied to syntax. In this paper, we propose a two-level approach to exploiting predicate-argument structure reordering in a hierarchical phrase-based translation model. First, we introduce linguistically motivated constraints into a hierarchical model, guiding translation phrase …...

This paper examines the efficacy of the appli- cation of a pre-existing technique in the area of event-event temporal relationship identifi- cation. We attempt to both reproduce the re- sults of said technique, as well as extend the previous work with application to a newly- created domain of biographical data. …...

We examine predicative adjectives as an unsu- pervised criterion to extract subjective adjec- tives. We do not only compare this criterion with a weakly supervised extraction method but also with gradable adjectives, i.e. another highly subjective subset of adjectives that can be extracted in an unsupervised fashion. In or- der …...

Bilingual dictionaries are expensive resources and not many are available when one of the languages is resource-poor. In this paper, we propose algorithms for creation of new reverse bilingual dictionaries from existing bilingual dictionaries in which English is one of the two languages. Our algorithms exploit the simi- larity between …...

Prior research into learning translations from source and target language monolingual texts has treated the task as an unsupervised learn- ing problem. Although many techniques take advantage of a seed bilingual lexicon, this work is the first to use that data for super- vised learning to combine a diverse set …...

We show that existing methods for training preposition error correction systems, whether using well-edited text or error-annotated cor- pora, do not generalize across very differ- ent test sets. We present a new, large error- annotated corpus and use it to train systems that generalize across three different test sets, each …...

We present a method for improving the perceived nat- uralness of corpus-based speech synthesizers. It con- sists in removing pronounced pitch peaks in the origi- nal recordings, which typically lead to noticeable dis- continuities in the synthesized speech. We perceptu- ally evaluated this method using two concatenative and two HMM-based …...

The rising influence of user-generated online reviews (Cone, 2011) has led to growing in- centive for businesses to solicit and manufac- ture DECEPTIVE OPINION SPAM—fictitious reviews that have been deliberately written to sound authentic and deceive the reader. Re- cently, Ott et al. (2011) have introduced an opinion spam dataset …...

LDA-frames is an unsupervised approach for identifying semantic frames from semanti- cally unlabeled text corpora, and seems to be a useful competitor for manually created databases of selectional preferences. The most limiting property of the algorithm is such that the number of frames and roles must be pre- defined. In …...

Social media texts are written in an infor- mal style, which hinders other natural lan- guage processing (NLP) applications such as machine translation. Text normalization is thus important for processing of social media text. Previous work mostly focused on nor- malizing words by replacing an informal word with its formal …...

In this paper, we study the problem of auto- matic enrichment of a morphologically under- specified treebank for Arabic, a morpholog- ically rich language. We show that we can map from a tagset of size six to one with 485 tags at an accuracy rate of 94%-95%. We can also …...

We report the results of our work on automat- ing the transliteration decision of named en- tities for English to Arabic machine trans- lation. We construct a classification-based framework to automate this decision, evalu- ate our classifier both in the limited news and the diverse Wikipedia domains, and achieve promising …...

We present a novel, structured language model - Supertagged Dependency Language Model to model the syntactic dependencies between words. The goal is to identify ungrammatical hypotheses from a set of candidate translations in a MT system combination framework and help select the best translation candidates using a variety of sentence-level …...

The many differences between Dialectal Ara- bic and Modern Standard Arabic (MSA) pose a challenge to the majority of Arabic natural language processing tools, which are designed for MSA. In this paper, we retarget an exist- ing state-of-the-art MSA morphological tag- ger to Egyptian Arabic (ARZ). Our evalua- tion demonstrates …...