AI-102 Plan and manage an Azure AI solution Practice Question
Which TWO Azure AI services can be used together to build a solution that transcribes customer service calls and detects sentiment?
⚠ Common exam trap
It's easy for candidates to confuse Azure AI Speech's text-to-speech with speech-to-text, or mistakenly think Azure AI Translator or conversational language understanding can perform sentiment analysis, when in fact only the specific sentiment analysis feature of Azure AI Language is designed for that task.
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
✓
Azure AI Language (sentiment analysis)
Azure AI Speech's speech-to-text capability transcribes the audio of customer service calls into text, while Azure AI Language's sentiment analysis evaluates that text to determine the overall sentiment (e.g., positive, negative, or neutral). Together, they form a complete pipeline for analyzing call recordings. Option A is correct because sentiment analysis is the specific feature within Azure AI Language that detects sentiment from text. Option B is correct because speech-to-text is the specific feature within Azure AI Speech that converts audio to text.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Azure AI Language (sentiment analysis)
Why this is correct
Analyzes sentiment from text.
- ✓
Azure AI Speech (speech-to-text)
Why this is correct
Transcribes audio.
- ✗
Azure AI Translator
Why it's wrong here
Translates text, not transcribes.
- ✗
Azure AI Speech (text-to-speech)
Why it's wrong here
Synthesizes speech, not transcribes.
- ✗
Azure AI Language (conversational language understanding)
Why it's wrong here
Understands intents, not sentiment.
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