Articles

AbstractThis paper proposes a method for improving the results of a statistical Machine Translation system using boundedness, a pragmatic component of the verbal phrase’s lexical aspect. First, the paper presents manual and automatic annotation experiments for lexical aspect in EnglishFrench parallel corpora. It will be shown that this aspectual property …...

AbstractQuantification (see e.g. Peters and Westerst ̊ahl, 2006) is probably one of the most extensively studied phenomena in formal semantics. But because of the specific representation of meaning assumed by modeltheoretic semantics (one where a true model of the world is a priori available), research in the area has primarily …...

AbstractVerb phrase (VP) ellipsis is the omission of a verb phrase whose meaning can be reconstructed from the linguistic or real-world context. It is licensed in English by auxiliary verbs, often modal auxiliaries: She can go to Hawaii but he can’t [e]. This paper describes a system called ViPER (VP …...

AbstractAbstract syntax is a semantic tree representation that lies between parse trees and logical forms. It abstracts away from word order and lexical items, but contains enough information to generate both surface strings and logical forms. Abstract syntax is commonly used in compilers as an intermediate between source and target …...

Vectorial representations of words have grown remarkably popular in natural language process- ing and machine translation. The recent surge in deep learning-inspired methods for producing distributed representations has been widely noted even outside these fields. Existing repre- sentations are typically trained on large monolingual corpora using context-based prediction models. In …...

We show that applying semantic role label constraints to bracketing ITG alignment to train MT systems improves the quality of MT output in comparison to the conventional BITG and GIZA alignments. Moreover, we show that applying soft constraints to SRL-constrained BITG alignment leads to a better translation system compared to …...

The statistical machine translation outputs are not error-free and in a high quality yet. So in the cases that we need high quality translations we definitely need the human intervention. An interactive-predictive machine translation is a framework, which enables the collabora- tion of the human and the translation system. Here, …...

Phrase–based machine translation (PBMT) relies upon the phrase-table as the main resource for bilingual knowledge at decoding time. A phrase table in its basic form includes aligned phrases along with four probabilities indicating aspects of the co-occurrence statistics for each phrase pair. In this paper we add a new semantic …...

We propose an improved beam search decoding algorithm with constrained softmax operations for neural machine translation (NMT). NMT is a newly emerging approach to predict the best translation by building a neural network instead of a log-linear model. It has achieved com- parable translation quality to the existing phrase-based statistical …...

We propose a novel pipeline for translation into morphologically rich languages which consists of two steps: initially, the source string is enriched with target morphological features and then fed into a translation model which takes care of reordering and lexical choice that matches the provided morphological features. As a proof …...

We describe effort to improve machine translation of item titles found in a large e-commerce inventory through topic modeling and adaptation. Item titles are short texts which typically contain brand names that do not have to be translated, and item attributes whose translation often depends on the context. Both issues …...

In this paper, we present a way of translating Korean words to Chinese using Chinese charac- ter information. A mapping table of Korean and Chinese characters is constructed and used to obtain possible combinations as translation candidates. The candidates are ranked by the combination score which accounts for the possibility …...

Domain adaptation boosts translation quality on in-domain data, but translation quality for domain adapted systems on out-of-domain data tends to suffer. Users of web-based translation services expect high quality translation across a wide range of diverse domains, and what makes the task even more difficult is that no domain label …...

Recent efforts to improve two-way speech-to-speech translation (S2S) systems have fo- cused on developing error detection and interactive error recovery capabilities. This article describes our current work on developing an eyes-free English-Iraqi Arabic S2S system that detects ASR errors and attempts to resolve them by eliciting user feedback. Here, we …...

This paper presents a novel approach to machine translation evaluation by combining register features – characterised by particular distributions of lexico-grammatical features – with text classification techniques. The goal of this method is to compare machine translation output with comparable originals in the same language, as well as with human …...

Shallow local multi-bottom up tree transducers (MBOTs) have been successfully used as trans- lation models in several settings because of their ability to model discontinuities. In this con- tribution, several additional settings are explored and evaluated. The first rule extractions for tree-to-tree MBOT with non-minimal rules and for string-to-string MBOT …...

Phrase-based machine translation can be configured to produce alignment data that indicates which machine translated target language words correspond to which original source language words. In most prior work that examined the efficacy of post-editing machine translation, post- editors were presented with machine translations (and in most cases the original …...

Post-editing the output of a statistical machine translation (SMT) system to obtain high-quality translation has become an increasingly common application of SMT, which henceforth we re- fer to as post-editing-based SMT (PE-SMT). PE-SMT is often deployed as an incrementally retrained system that can learn knowledge from human post-editing outputs as …...

We present an approach to structured prediction from bandit feedback, called Bandit Structured Prediction, where only the value of a task loss function at a single predicted point, instead of a correct structure, is observed in learning. We present an application to discriminative rerank- ing in Statistical Machine Translation (SMT) …...

Lexical sparsity is a major challenge for machine translation into morphologically rich lan- guages. We address this problem by modeling sequences of fine-grained morphological tags in a bilingual context. To overcome the issue of ambiguous word analyses, we introduce soft tags, which are under-specified representations retaining all possible morphological attributes …...