Papers Multilingual Word Embeddings
“Multilingual Word Embeddings” 태그가 달린 논문 57편 · 필터 해제
Aligning Multilingual Word Embeddings for Cross-Modal Retrieval Task
In this paper, we propose a new approach to learn multimodal multilingual embeddings for matching images and their relevant captions in two languages. We combine two existing objective functions to make images and captio…
Cross-Modal RetrievalImage to textImage-to-Text RetrievalMultilingual Word Embeddings+3Toward Multilingual Identification of Online Registers
We consider cross- and multilingual text classification approaches to the identification of online registers (genres), i.e. text varieties with specific situational characteristics. Register is the most important predict…
Multilingual text classificationMultilingual Word Embeddingstext-classificationText Classification+1Learning Unsupervised Multilingual Word Embeddings with Incremental Multilingual Hubs
Recent research has discovered that a shared bilingual word embedding space can be induced by projecting monolingual word embedding spaces from two languages using a self-learning paradigm without any bilingual supervisi…
Bilingual Lexicon InductionCross-Lingual Word EmbeddingsDependency ParsingDocument Classification+3EusDisParser: improving an under-resourced discourse parser with cross-lingual data
Development of discourse parsers to annotate the relational discourse structure of a text is crucial for many downstream tasks. However, most of the existing work focuses on English, assuming a quite large dataset. Disco…
Multilingual Word EmbeddingsWord EmbeddingsLearning Multilingual Word Embeddings Using Image-Text Data
There has been significant interest recently in learning multilingual word embeddings -- in which semantically similar words across languages have similar embeddings. State-of-the-art approaches have relied on expensive …
Multilingual Word EmbeddingsSemantic SimilaritySemantic Textual SimilarityWord EmbeddingsUnsupervised Hyper-alignment for Multilingual Word Embeddings
We consider the problem of aligning continuous word representations, learned in multiple languages, to a common space. It was recently shown that, in the case of two languages, it is possible to learn such a mapping with…
Multilingual Word EmbeddingsTranslationWord EmbeddingsWord TranslationZero-Shot Cross-Lingual Opinion Target Extraction
Aspect-based sentiment analysis involves the recognition of so called opinion target expressions (OTEs). To automatically extract OTEs, supervised learning algorithms are usually employed which are trained on manually an…
Aspect-Based Sentiment AnalysisAspect-Based Sentiment Analysis (ABSA)Multilingual Word EmbeddingsSentiment Analysis+1Expanding the Text Classification Toolbox with Cross-Lingual Embeddings
Most work in text classification and Natural Language Processing (NLP) focuses on English or a handful of other languages that have text corpora of hundreds of millions of words. This is creating a new version of the dig…
ClassificationGeneral ClassificationIntent DetectionMultilingual Word Embeddings+4Learning multilingual topics through aspect extraction from monolingual texts
Unsupervised Hyperalignment for Multilingual Word Embeddings
We consider the problem of aligning continuous word representations, learned in multiple languages, to a common space. It was recently shown that, in the case of two languages, it is possible to learn such a mapping with…
Multilingual Word EmbeddingsTranslationWord EmbeddingsWord TranslationGlobalTrait: Personality Alignment of Multilingual Word Embeddings
We propose a multilingual model to recognize Big Five Personality traits from text data in four different languages: English, Spanish, Dutch and Italian. Our analysis shows that words having a similar semantic meaning in…
Multilingual Word EmbeddingsPersonality AlignmentWord EmbeddingsMultilingual Embeddings Jointly Induced from Contexts and Concepts: Simple, Strong and Scalable
Word embeddings induced from local context are prevalent in NLP. A simple and effective context-based multilingual embedding learner is Levy et al. (2017)'s S-ID (sentence ID) method. Another line of work induces high-pe…
Multilingual Word EmbeddingsSentenceWord EmbeddingsCross-lingual Lexical Sememe Prediction
Sememes are defined as the minimum semantic units of human languages. As important knowledge sources, sememe-based linguistic knowledge bases have been widely used in many NLP tasks. However, most languages still do not …
Learning Word EmbeddingsMultilingual Word EmbeddingsPredictionWord EmbeddingsNORMA: Neighborhood Sensitive Maps for Multilingual Word Embeddings
Inducing multilingual word embeddings by learning a linear map between embedding spaces of different languages achieves remarkable accuracy on related languages. However, accuracy drops substantially when translating bet…
Machine TranslationMultilingual Word EmbeddingsTranslationWord Embeddings+1Learning Unsupervised Word Translations Without Adversaries
Word translation, or bilingual dictionary induction, is an important capability that impacts many multilingual language processing tasks. Recent research has shown that word translation can be achieved in an unsupervised…
Machine TranslationMultilingual Word EmbeddingsSensitivityTransfer Learning+3Unsupervised Multilingual Word Embeddings
Multilingual Word Embeddings (MWEs) represent words from multiple languages in a single distributional vector space. Unsupervised MWE (UMWE) methods acquire multilingual embeddings without cross-lingual supervision, whic…
Multilingual Word EmbeddingsTranslationWord EmbeddingsWord Similarity+1Learning Multilingual Word Embeddings in Latent Metric Space: A Geometric Approach
We propose a novel geometric approach for learning bilingual mappings given monolingual embeddings and a bilingual dictionary. Our approach decouples learning the transformation from the source language to the target lan…
Bilingual Lexicon InductionMultilingual Word EmbeddingsRecommendation SystemsTranslation+3Orthographic Features for Bilingual Lexicon Induction
Recent embedding-based methods in bilingual lexicon induction show good results, but do not take advantage of orthographic features, such as edit distance, which can be helpful for pairs of related languages. This work e…
Bilingual Lexicon InductionMachine TranslationMultilingual Word EmbeddingsUnsupervised Machine Translation+2