Generalizing Procrustes Analysis for Better Bilingual Dictionary Induction
Most recent approaches to bilingual dictionary induction find a linear alignment between the word vector spaces of two languages. We show that projecting the two languages onto a third, latent space, rather than directly onto each other, while equivalent in terms of expressivity, makes it easier to learn approximate alignments. Our modified approach also allows for supporting languages to be included in the alignment process, to obtain an even better performance in low resource settings.
Code (1)
Similar Papers 제목 키워드 기반
A Multi-Pairwise Extension of Procrustes Analysis for Multilingual Word Translation
In this paper we present a novel approach to simultaneously representing multiple languages in a common space. Procrustes Analysis (PA) is commonly used to find the optimal orthogonal word mapping in the bilingual case. …
TranslationWord TranslationA Locally Linear Procedure for Word Translation
Learning a mapping between word embeddings of two languages given a dictionary is an important problem with several applications. A common mapping approach is using an orthogonal matrix. The Orthogonal Procrustes Analysi…
TranslationWord EmbeddingsWord SimilarityWord TranslationBilingual Dictionary Based Neural Machine Translation without Using Parallel Sentences
In this paper, we propose a new task of machine translation (MT), which is based on no parallel sentences but can refer to a ground-truth bilingual dictionary. Motivated by the ability of a monolingual speaker learning t…
Machine TranslationTranslationWord TranslationAdaptive Dictionary for Bilingual Lexicon Extraction from Comparable Corpora
One of the main resources used for the task of bilingual lexicon extraction from comparable corpora is : the bilingual dictionary, which is considered as a bridge between two languages. However, no particular attention h…
Information RetrievalDict-NMT: Bilingual Dictionary based NMT for Extremely Low Resource Languages
Neural Machine Translation (NMT) models have been effective on large bilingual datasets. However, the existing methods and techniques show that the model's performance is highly dependent on the number of examples in tra…
Machine TranslationNMTTranslation