Multi-Lingual Word Alignment Prediction
Word alignment prediction is the process of associating (mapping) words from some primary text with corresponding words in a secondary text. his tool uses statistical algorithms to determine which words or phrases in two texts are equivalent in meaning.
With wordMAP you can create amazing translation tools that:
- Ensure all terms and phrases in the primary text have a proper translation in the secondary text.
- Provide in-context vocabulary suggestions to the translator.
- Helps prevent inconsistencies in the translation.
- Pre-translates text.
yarn add wordmap
Here's a minimum setup example.
const map = new WordMAP(); map.appendAlignmentMemoryString("Tag", "day"); const source = "Guten Tag"; const target = "Good morning"; const suggestions = map.predict(source, target); console.log(suggestions.toString()); // produces -> "0 [0|n:guten->n:good] [0|n:tag->n:morning]"
- Aligning a primary text with a secondary text e.g. when generating word maps for gateway languages.
- Aligning a secondary text with a ternary text.
- Aligning a primary text to a ternary text (using the secondary as a proxy)
Existing tools require large data sets, complex running environments, and are usually limited to running in a server environment.
We need a tool that:
- runs on the client with minimal configuration.
- works with existing web browser technology.
- integrates with translationCore and related tools.
- works without an Internet connection.
- does not have a minimum corpus size.
- requires minimal system resources.
Want to learn more? Read WHITEPAPER.md.
When publishing to npm be sure to use the command
This will publish the proper module structure to npm.