Compound Word Splitting for Machine Translation Alignment

The patent applies segmentation by dividing compound words into their constituent parts (morphemes) before translation. The system identifies split points in compound words and separates them into individual components, allowing each component to be translated independently. This resolves the alignment problem by transforming a single compound word token into multiple translatable units, enabling the phrase-based statistical process to handle compound words effectively while maintaining translation efficiency.

The patent implements a dynamic translation approach where the system adaptively determines whether to translate compound words as single units or split them into components based on the target language characteristics. The system dynamically adjusts its processing mode: for languages that use compound words, it maintains single-unit translation for speed; for languages that don't use compound words, it automatically segments and translates components separately, thereby optimizing both speed and quality based on the specific translation context.

The patent implements a self-service mechanism where the system automatically learns and stores morphological operations from parallel corpora during training. The system independently identifies common morphological patterns (such as linking elements, prefixes, and suffixes) and creates a lookup table of these operations. During translation, the system simply queries this pre-computed table rather than performing complex real-time analysis, thereby achieving high translation accuracy while keeping the operational complexity low through automated self-learning and caching.