AI-102 Practice Question: Implement natural language processing solutions
You are developing a multilingual chatbot that must understand user intents in English, Spanish, and French. You are using the Azure AI Language service with a Conversational Language Understanding (CLU) project. What is the recommended approach to handle multiple languages?
⚠ Common exam trap
Candidates often assume translation or separate projects are necessary for multilingual support, overlooking that Azure CLU's built-in multi-lingual detection is the simpler and more accurate solution, as Microsoft explicitly recommends using a single multi-lingual project over translation or project duplication.
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Add utterances in all three languages to the CLU project and enable multi-lingual detection.
The Azure AI Language service's Conversational Language Understanding (CLU) supports multi-lingual projects natively. By adding utterances in English, Spanish, and French to a single CLU project and enabling multi-lingual detection, the model learns to recognize intents across languages without needing separate projects or translation steps. This approach leverages the underlying multilingual BERT-based model, which shares language-agnostic representations, making it the recommended and most efficient method.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Use Azure AI Translator to translate all input to English before sending to CLU.
Why it's wrong here
Adds latency and may lose language-specific nuances.
- ✓
Add utterances in all three languages to the CLU project and enable multi-lingual detection.
Why this is correct
CLU can be trained with multiple languages and detect language automatically.
- ✗
Use the Translator service to detect language and route to language-specific CLU endpoints.
Why it's wrong here
Overly complex; CLU can handle all languages in one project.
- ✗
Create separate CLU projects for each language.
Why it's wrong here
Not needed; CLU supports multiple languages in one project.
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