如何针对非英语语言训练Wit.ai并输入对应语言脚本？

Great question! I’ve worked with Wit.ai on multilingual projects before, so let me walk you through how to do this properly—no more transliterating, you can use native scripts directly.

Whether you’re starting a new app or modifying an existing one, getting set up for native script input is straightforward:

• When creating a new Wit.ai app, look for the Language dropdown in the setup flow. Select your target language (e.g., Japanese, Hindi, Portuguese) here, and the platform will immediately accept content in its native script.
• For an existing app, click the gear icon in the top-right corner to open your app’s Settings. Navigate to the Language section, switch to your desired language, and save changes. Wit.ai will automatically render and process native script text after this update.

Once your app is set to the right language, training with native content works just like English—here’s how to do it effectively:

• Add utterances in native script: When building intents, type or paste example phrases directly using the language’s native characters. For a German model, that means inputting utterances like Ich möchte einen Tisch für zwei reservieren instead of translating to English.
• Define entities with native values: For entities (e.g., product names, dates, locations), input their native script versions. A Korean restaurant entity could have values like 김밥천국 or 보쌈집—no need for English equivalents.
• Handle multiple languages with separate apps: Wit.ai doesn’t support multi-language models in a single app natively. If you need your assistant to work across several languages, create a dedicated app for each. This lets you tailor training examples to each language’s unique phrasing and context.
• Test with native queries: Use the test panel to input queries in the native language. The results will display in the same script, making it easy to verify that Wit.ai correctly identifies intents and entities.

A quick note: While Wit.ai supports most major languages with native scripts, double-check their supported languages list first. For less common languages, you may need to add more training examples to help the model learn patterns and improve accuracy.

内容的提问来源于stack exchange，提问作者coderoda