Articles

We propose in this paper a method for quantifying sentence grammaticality. The approach based on Property Grammars, a constraint-based syntactic formalism, makes it possible to evaluate a grammat- icality index for any kind of sentence, in- cluding ill-formed ones. We compare on a sample of sentences the grammaticality indices obtained …...

It has previously been assumed in the psycholinguistic literature that finite-state models of language are crucially limited in their explanatory power by the local- ity of the probability distribution and the narrow scope of information used by the model. We show that a simple computa- tional model (a bigram part-of-speech …...

Combination methods are an effective way of improving system performance. This paper examines the benefits of system combination for unsupervised WSD. We investigate several voting- and arbiter- based combination strategies over a di- verse pool of unsupervised WSD systems. Our combination methods rely on predom- inant senses which are derived …...

Syntactic knowledge is important for pro- noun resolution. Traditionally, the syntac- tic information for pronoun resolution is represented in terms of features that have to be selected and defined heuristically. In the paper, we propose a kernel-based method that can automatically mine the syntactic information from the parse trees for …...

We present an approach to pronoun reso- lution based on syntactic paths. Through a simple bootstrapping procedure, we learn the likelihood of coreference between a pronoun and a candidate noun based on the path in the parse tree between the two en- tities. This path information enables us to handle …...

We present a novel method for extract- ing parallel sub-sentential fragments from comparable, non-parallel bilingual cor- pora. By analyzing potentially similar sentence pairs using a signal processing- inspired approach, we detect which seg- ments of the source sentence are translated into segments in the target sentence, and which are not. …...

We consider the task of unsupervised lec- ture segmentation. We formalize segmen- tation as a graph-partitioning task that op- timizes the normalized cut criterion. Our approach moves beyond localized com- parisons and takes into account long- range cohesion dependencies. Our results demonstrate that global analysis improves the segmentation accuracy and …...

We present a method for unsupervised topic modelling which adapts methods used in document classification (Blei et al., 2003; Griffiths and Steyvers, 2004) to unsegmented multi-party discourse tran- scripts. We show how Bayesian infer- ence in this generative model can be used to simultaneously address the prob- lems of topic …...

This paper presents an extensive evalua- tion of five different alignments and in- vestigates their impact on the correspond- ing MT system output. We introduce new measures for intrinsic evaluations and examine the distribution of phrases and untranslated words during decoding to identify which characteristics of different alignments affect translation. …...

Statistical machine translation is quite ro- bust when it comes to the choice of in- put representation. It only requires con- sistency between training and testing. As a result, there is a wide range of possi- ble preprocessing choices for data used in statistical machine translation. This is even more …...

AbstractRecent improvements in speech recognition technology have resulted in products that can now demonstrate commercial value in a variety of applications. Many vendors are marketing products which combine ASR applications including continuous dictation, command-and-control interfaces, and transcription of recorded speech at an accuracy of 98%. In this study, we measured …...

AbstractThis paper reports on prosodic evaluation in the framework of the EVALDA/EvaSy project for text-to-speech (TTS) evaluation for the French language. Prosody is evaluated using a prosodic transplantation paradigm. Intonation contours generated by the synthesis systems are transplanted on a common segmental content. Both diphone based synthesis and natural speech …...

AbstractMost African countries follow an oral tradition system to transmit their cultural, scientific and historic heritage through generations. This ancestral knowledge accumulated during centuries is today threatened of disappearing. This paper presents the first steps in the building of an automatic speech to text transcription for African oral patrimony, particularly …...

AbstractThis paper reports a large-scale non-probabilistic parsing experiment with a deep LFG parser. We briefly introduce the parser we used, named SXLFG, and the resources that were used together with it. Then we report quantitative results about the parsing of a multi-million word journalistic corpus. We show that we can …...

AbstractItalWordNet (IWN) and PAROLE/SIMPLE/CLIPS (PSC), the two largest electronic, general-purpose lexical resources of Italian language present many compatible aspects although they are based on two different lexical models having their own underlying principles and peculiarities. Such compatibility prompted us to study the feasibility of semi-automatically linking and eventually merging the …...

Query Expansion was designed to overcome the barren query words issued by user and has been applied in many commercial products. This treatment tries to expand query words to identify users’ real requirement based on semantic computation. It may be critical to deal with the problem of information overloading and …...

In this paper, a new robust wavelet-based voice activity detection (VAD) algorithm derived from the discrete wavelet transform (DWT) and Teager energy operation (TEO) processing is presented. We decompose the speech signal into four subbands by using the DWT. By means of the multi-resolution analysis property of the DWT, the …...

There are many methods to improve performances of statistical parsers. Among them, resolving structural ambiguities is a major task. In our approach, the parser produces a set of n-best trees based on a feature-extended PCFG grammar and then selects the best tree structure based on association strengths of dependency word-pairs. …...

In this paper we study the problem of learning context-free grammar from a cor- pus. We investigate a technique that is based on the notion of minimum description length of the corpus. A cost as a function of grammar is defined as the sum of the number of bits required …...

The segment model (SM) is a family of methods that use the segmental distribution rather than frame-based density (e.g. HMM) to represent the underlying characteristics of the observation sequence. It has been proved to be more precise than HMM. However, their high level of complexity prevents these models from being …...