In this paper we describe and evaluate different statistical models for the task of realization ranking, i.e. the problem of discriminating between competing surface realizations generated for a given input semantics. Three models are trained and tested; an n-gram language model, a discriminative maximum entropy model using structural features, and a combination of these two. Our realization co...

Recent challenges to Chomsky's poverty of the stimulus thesis for language acquisition suggest that children's primary data may carry "indirect evidence" about linguistic constructions despite containing no instances of them. Indirect evidence is claimed to suffice for grammar acquisition, without need for innate knowledge. This article reports experiments based on those of Reali and Christians...

the present study intended to propose a causal model of factors that would predict oral communication apprehension (oca) of iranian learners of english as a foreign language. to conduct the study, 135 male and female university students majoring in english were selected. five variables including: learners’self-esteem and introversion/extroversion(as independent variables), their gender and prof...

The agreement in gender and number is a critical problem in statistical language modeling. One of the main problems in the speech recognition of French language is the presence of misrecognized words due to the bad agreement (in gender and number) between words. Statistical language models do not treat this phenomena directly. This paper focuses on how to handle the issue of agreements. We intr...

Recent challenges to Chomsky’s poverty of the stimulus thesis for language acquisition suggest that children’s primary data may carry ‘indirect evidence’ about linguistic constructions despite containing no instances of them. Indirect evidence is claimed to suffice for grammar acquisition, without need for innate knowledge or specialized learning mechanisms. We report experiments based on those...

This paper presents example-based machine translation (MT) based on syntactic transfer, which selects the best translation by using models of statistical machine translation. Example-based MT sometimes generates invalid translations because it selects similar examples to the input sentence based only on source language similarity. The method proposed in this paper selects the best translation b...

We introduce a graphical language for relational data called the probabilistic entityrelationship (PER) model. The model is an extension of the entity-relationship model, a common model for the abstract representation of database structure. We concentrate on the directed version of this model—the directed acyclic probabilistic entity-relationship (DAPER) model. The DAPER model is closely relate...

In this paper we describe and evaluate several statistical models for the task of realization ranking, i.e. the problem of discriminating between competing surface realizations generated for a given input semantics. Three models (and several variants) are trained and tested: an n-gram language model, a discriminative maximum entropy model using structural information (and incorporating the lang...

I present three well-known probabilistic models of information retrieval in tutorial style: The binary independence probabilistic model, the language modeling approach, and Google’s page rank. Although all three models are based on probability theory, they are very different in nature. Each model seems well-suited for solving certain information retrieval problems, but not so useful for solving...

Dialogue systems are one of the most challenging applications of Natural Language Processing. In recent years, some statistical dialogue models have been proposed to cope with the dialogue problem. The evaluation of these models is usually performed by using them as annotation models. Many of the works on annotation use information such as the complete sequence of dialogue turns or the correct ...