Multilingual Word Embeddings

Multilingual Word Embeddings are a method of cross-lingual word representation that aims to capture semantic and syntactic relationships between words in different languages, enabling efficient semantic alignment and information sharing across multiple linguistic environments. The core objective is to construct a unified vector space where words from different languages have similar representations, thereby supporting cross-lingual tasks such as information retrieval, machine translation, and sentiment analysis in natural language processing. This approach can significantly enhance the performance and generalization capabilities of multilingual applications, fostering better language understanding and communication on a global scale.