Abstract Cross-lingual summarization is the task of generating a summary in one language (e.g., English) for given document(s) different Chinese). Under globalization background, this has attracted increasing attention computational linguistics community. Nevertheless, there still remains lack comprehensive review task. Therefore, we present first systematic critical on datasets, approaches, an...

This article deals with the problem of Cross-Lingual Text Categorization (CLTC), which arises when documents in different languages must be classified according to the same classification tree. We describe practical and cost-effective solutions for automatic Cross-Lingual Text Categorization, both in case a sufficient number of training examples is available for each new language and in the cas...

CROSS-LINGUAL VOICE CONVERSION Cross-lingual voice conversion refers to the automatic transformation of a source speaker’s voice to a target speaker’s voice in a language that the target speaker can not speak. It involves a set of statistical analysis, pattern recognition, machine learning, and signal processing techniques. This study focuses on the problems related to cross-lingual voice conve...

This paper presents a languageindependent approach to controlled vocabulary keyword assignment using the EUROVOC thesaurus. Due to the multilingual nature of EUROVOC, the keywords for a document written in one language can be displayed in all eleven official European Union languages. The mapping of documents written in different languages to the same multilingual thesaurus furthermore allows cr...

We investigate in this paper the degree of overlap between synonym sets of translated word pairs across three languages: French, English and Romanian. We use for this purpose a French Synonym Dictionary, a Romanian Synonym Dictionary, Princeton’s WordNet and Google Translate API. We build a database containing pairs of (translated) words from the three languages, along with their corresponding ...

Cross-lingual embedding models allow us to project words from different languages into a shared embedding space. This allows us to apply models trained on languages with a lot of data, e.g. English to low-resource languages. In the following, we will survey models that seek to learn cross-lingual embeddings. We will discuss them based on the type of approach and the nature of parallel data that...

Cross-lingual natural language processing hinges on the premise that there exists invariance across languages. At the word level, researchers have identified such invariance in the word embedding semantic spaces of different languages. However, in order to connect the separate spaces, cross-lingual supervision encoded in parallel data is typically required. In this paper, we attempt to establis...

The cyberspace is populated with valuable information sources, expressed in about 1500 different languages and dialects. Yet, for the vast majority of WEB surfers this wealth of information is practically inaccessible or meaningless. Recent advancements in cross-lingual information retrieval, multilingual summarization, cross-lingual question answering and machine translation promise to narrow ...

We release a cross-lingual wikification system for all languages in Wikipedia. Given a piece of text in any supported language, the system identifies names of people, locations, organizations, and grounds these names to the corresponding English Wikipedia entries. The system is based on two components: a cross-lingual named entity recognition (NER) model and a crosslingual mention grounding mod...

In this paper, we introduce our cross-lingual linked data lexica, called xLiD-Lexica, which are constructed by exploiting the multilingual Wikipedia and linked data resources from Linked Open Data (LOD). We provide the cross-lingual groundings of linked data resources from LOD as RDF data, which can be easily integrated into the LOD data sources. In addition, we build a SPARQL endpoint over our...