Лог-линейная модель

Based upon a statistically trained speech translation system, in this study, we try to combine distinctive features derived from the two modules: speech recognition and statistical machine translation, in a …...

This paper describes the role of supertagging in a wide-coverage CCG parser which uses a log-linear model to select an analysis. The supertagger reduces the derivation space over which model …...

. This paper describes a method of adapting a domain-inde- pendent HPSG parser to a biomedical domain. Without modifying the grammar and the probabilistic model of the original HPSG parser, …...

. In this paper, we present an empirical study that utilizes morph-syntactical information to improve translation quality. With three kinds of language pairs matched according to morph-syntactical similar- ity or …...

This paper reports the NTT statistical translation system par- ticipating in the evaluation campaign of IWSLT 2005. The NTT system is based on a phrase translation model and uti- lizes …...

The Microsoft Research translation system is a syntactically informed phrasal SMT system that uses a phrase translation model based on dependency treelets and a global reordering model based on the …...

We describe the experiments of the UC Berke- ley team on improving English-Spanish ma- chine translation of news text, as part of the WMT’08 Shared Translation Task. We ex- periment …...

In this work, the problem of extracting phrase translation is formulated as an information re- trieval process implemented with a log-linear model aiming for a balanced precision and re- call. …...

Paraphrase patterns are useful in paraphrase recognition and generation. In this paper, we present a pivot approach for extracting para- phrase patterns from bilingual parallel cor- pora, whereby the English …...

System combination has emerged as a powerful method for machine translation (MT). This paper pursues a joint optimization strategy for combining outputs from multiple MT systems, where word alignment, ordering, …...

Morphological segmentation breaks words into morphemes (the basic semantic units). It is a key component for natural language pro- cessing systems. Unsupervised morphologi- cal segmentation is attractive, because in ev- …...

AbstractIn this paper we present an experimental toolbox for automatic tree-to-tree alignment based on a binary classification model. The aligner implements a recurrent architecture for structural prediction using history features …...

Source language reordering can be seen as the preprocessing task of permuting the or- der of the source words in such a way that the resulting permutation allows as mono- …...

AbstractA key aspect in the development of statistical translators is the synergic combination of different sources of knowledge. This work describes the effect and implications that would have adding additional …...

This paper proposes a new method for ap- proximate string search, specifically candidate generation in spelling error correction, which is a task as follows. Given a misspelled word, the system …...

Efficient decoding for syntactic parsing has become a necessary research area as statisti- cal grammars grow in accuracy and size and as more NLP applications leverage syntac- tic analyses. We …...

This paper presents an integrated, end-to-end approach to online spelling correction for text input. Online spelling correction refers to the spelling correction as you type, as opposed to post-editing. The …...

Previous work on paraphrase extraction and application has relied on either parallel datasets, or on distributional similarity met- rics over large text corpora. Our approach combines these two orthogonal sources …...

We present a unified unsupervised statistical model for text normalization. The relation- ship between standard and non-standard to- kens is characterized by a log-linear model, permitting arbitrary features. The weights …...

In this paper, we propose a joint segmenta- tion and classification framework for sen- timent analysis. Existing sentiment clas- sification algorithms typically split a sen- tence as a word sequence, …...

AbstractWe present a dynamic programming algorithm for efficient constrained inference in semantic role labeling. The algorithm tractably captures a majority of the structural constraints examined by prior work in this …...

This paper presents a new algorithm to automatically solve algebra word prob- lems. Our algorithm solves a word prob- lem via analyzing a hypothesis space con- taining all possible equation …...

The log-linear combination of different features is an important component of SMT systems. It allows for the easy in- tegartion of models into the system and is used during decoding …...

In this work, we explore how learners can infer second-language noun meanings in the context of their native language. Mo- tivated by an interest in building interac- tive tools for …...

AbstractIn recent years, several end-to-end online translation systems have been proposed to successfully incorporate human post-editing feedback in the translation workflow. The performance of these systems in a multi-domain translation …...

AbstractAlthough neural machine translation has made significant progress recently, how to integrate multiple overlapping, arbitrary prior knowledge sources remains a challenge. In this work, we propose to use posterior regularization …...

AbstractTo enrich vocabulary of low resource settings, we proposed a novel method which identify loanwords in monolingual corpora. More specifically, we first use cross-lingual word embeddings as the core feature …...

AbstractMethods for erasing human-interpretable concepts from neural representations that assume linearity have been found to be tractable and useful. However, the impact of this removal on the behavior of downstream …...