Microsoft Certified: Azure AI Engineer AssociateImplement natural language processing solutionsMedium
A retail company wants to analyze product reviews submitted by customers in multiple languages to understand common complaints and feature requests. The solution needs to automatically translate reviews into English before performing sentiment analysis and key phrase extraction. Which sequence of Azure AI services should be used?
- AAzure AI Speech -> Azure AI Language (Sentiment & Key Phrase)
- BAzure AI Language (Sentiment & Key Phrase) -> Azure Translator
- CAzure Translator -> Azure AI Language (Sentiment & Key Phrase)
- DAzure Bot Service -> Azure Translator
Show answer & explanationAnswer & explanation
Correct answer: C. Azure Translator -> Azure AI Language (Sentiment & Key Phrase)
To analyze reviews in multiple languages, they must first be translated into a common language (English, as specified). Azure Translator performs this translation. Once translated, Azure AI Language can then perform sentiment analysis and key phrase extraction on the unified English text.
Why the other options are wrong
- A. Azure AI Speech is for converting speech to text or text to speech, not for text translation or analysis.
- B. Performing sentiment/key phrase extraction before translation would analyze the original language, not the desired English context.
- D. Azure Bot Service is for building conversational bots and is not directly involved in this text processing pipeline.
Multilingual Text Analysis Pipeline
A common workflow for analyzing text in multiple languages, typically involving translation to a common language followed by natural language processing (NLP) tasks.
- Translation is usually the first step.
- Azure Translator for translation.
- Azure AI Language for NLP tasks.
Memory trick: Translate first, then understand with AI.