CLD2CLD3

CLD2CLD3 is an informal term for approaches that integrate the CLD2 and CLD3 language detection engines to improve reliability and coverage. The combination is not a single official product but a pattern used by developers to leverage the strengths of both detectors.

CLD2, Compact Language Detector 2, is an older detector derived from character n-gram statistics and a compact probabilistic model. It tends to be fast and robust across many languages and scripts, particularly with longer, well-formed text. It can be less reliable on very short inputs or on mixed-language content.

CLD3, Compact Language Detector 3, represents a newer neural-network-based detector designed to improve accuracy on short texts and in situations with less predictable language patterns. It generally provides better performance for short phrases and for languages that CLD2 struggles with, but may require more computational resources.

Practitioners composing CLD2CLD3 workflows may route text to CLD3 for short inputs or low-confidence results from CLD2, and/or combine results via a voting or confidence-weighted scheme. Some implementations use CLD3 as the primary detector for short sentences and use CLD2 as a fallback for longer documents or where speed is critical. Others perform ensemble decisions that require agreement between the two outputs.

Both detectors are available as open-source projects with permissive licenses and have been used in various software systems that require language identification, from blogs to content management tools and browser-related features. The CLD2CLD3 approach reflects a general preference for hybrid language-detection strategies to balance speed and accuracy across text lengths and languages.