Globalese

Overview

Globalese is a neural machine translation (NMT) engine training platform developed by CrossLang. It allows users to build and customize their own NMT engines using their translation memories and terminology. The platform is designed to provide high-quality, domain-specific machine translation.

Key Features

• Engine Training — Users can train NMT engines using their own translation memories and glossaries.
• Customization Options — Provides control over engine parameters to optimize translation quality for specific content types.
• Quality Estimation — Offers tools to assess the quality of machine translation output.
• API Integration — Enables integration of Globalese engines into existing translation workflows and tools.
• Project Management — Supports the organization and management of translation projects within the platform.

Who It's For

Globalese is designed for language service providers, corporate localization departments, and individual translators who require customized machine translation solutions. It targets organizations that possess significant volumes of high-quality linguistic data and aim to leverage NMT for improved efficiency and consistency in their translation processes.

Notable Strengths

A notable strength of Globalese is its focus on enabling users to build highly customized NMT engines from their proprietary data. This approach allows for the creation of domain-specific engines that can outperform generic NMT systems in terms of accuracy and style. The platform's API facilitates integration into various translation management systems and CAT tools, streamlining existing localization workflows.