A method is presented for automatically augmenting the bilingual lexicon of an existing Machine Translation system, by extracting bilingual entries from aligned bilingual text. The proposed method only relies on the resources already available in the MT system itself. It is based on the use of bilingual lexical templates to match the terminal symbols in the parses of the aligned sentences. 1 I ...

This paper is concerned with the task of bilingual lexicon induction using imagebased features. By applying features from a convolutional neural network (CNN), we obtain state-of-the-art performance on a standard dataset, obtaining a 79% relative improvement over previous work which uses bags of visual words based on SIFT features. The CNN image-based approach is also compared with state-of-the...

Statistical machine translation relies on the availability of substantial amounts of human translated texts. Such bilingual resources are available for relatively few language pairs, which presents obstacles to applying current statistical translation models to low-resource languages. In this work, we induce bilingual dictionaries from more plentiful monolingual corpora using a diverse set of c...

Prior research into learning translations from source and target language monolingual texts has treated the task as an unsupervised learning problem. Although many techniques take advantage of a seed bilingual lexicon, this work is the first to use that data for supervised learning to combine a diverse set of signals derived from a pair of monolingual corpora into a single discriminative model....

We present a MT system that applies graph unification in transfer from English to Finnish. The work described below is an outgrowth of a multilingual MT project initiated by the IBM in 1987 with the aim of studying multilingual translation using a common English language parser. The transfer system presented here is independent of the parsing and generation modules. Any source language parser c...

This paper describes a simple approach of statistical language modelling for bilingual lexicon acquisition from Amharic-English parallel corpora. The goal is to induce a seed translation lexicon from sentence-aligned corpora. The seed translation lexicon contains matches of Amharic lexemes to weekly inflected English words. Purely statistical measures of term distribution are used as the basis ...

A method is presented for automatically augmenting the bilingual lexicon of an existing Machine Translation system, by extracting bilingual entries from Migned bilingual text. The proposed method only relies on the resources already available in the MT system itself. It is based on the use of bilingual lexical templates to match the terminal symbols in the parses of the aligned sentences. 1 I n...

This paper introduces a new bilingual Czech-English verbal valency lexicon (called CzEngVallex) representing a relatively large empirical database. It includes 20,835 aligned valency frame pairs (i.e., verb senses which are translations of each other) and their aligned arguments. This new lexicon uses data from the Prague Czech-English Dependency Treebank and also takes advantage of the existin...

Bilingual lexicons are fundamental resources. Modern automated lexicon generation methods usually require parallel corpora, which are not available for most language pairs. Lexicons can be generated using non-parallel corpora or a pivot language, but such lexicons are noisy. We present an algorithm for generating a high quality lexicon from a noisy one, which only requires an independent corpus...

This paper introduces a method for learning bilingual term and sentence level alignments for the purpose of building bilingual lexicons. Combining statistical techniques with linguistic knowledge, a general algorithm is developed for learning term and sentence alignments from large bilingual corpora with high accuracy. This is achieved through the use of ltered linguistic feedback between term ...