Bridging global divides by converting language through the power of algorithms, statistics, and neural networks.
In a world with over 7,000 languages, mastering every language is impossible. Machine translation (MT) has emerged as an indispensable instrument for global connectivity.
At its core, MT aims to facilitate dialogue and information exchange, empowering individuals and organizations to communicate effectively regardless of linguistic background.
Reaching international markets and engaging global customers.
Making academic resources accessible worldwide.
Communicating with patients who speak different languages.
Understanding international treaties and agreements.
It's not just word-for-word substitution. It's a complex computational linguistic process.
Deciphering grammatical rules, syntactic structures, and analyzing the source text's structure.
Extracting semantic content. Dealing with nuances, metaphors, idioms, and cultural references.
Creating the target text using linguistic rules, statistical patterns, or deep learning models.
Assessing quality for fluency and adequacy. Learning from errors to improve future performance.
Built on exhaustive linguistic rules and lexicons (grammar, syntax, dictionaries). It breaks sentences down into constituent parts and reconstructs them using the target language's rules.
A data-driven approach that learns by analyzing vast volumes of bilingual text. It calculates the probability of a translation based on observed patterns in training data.
Uses deep learning and neural networks to model translation as a pattern recognition task. It encodes the source text into a vector (high-dimensional space) and decodes it into the target language.