Microsoft Certified: Azure AI Engineer AssociateImplement natural language processing solutionsMedium
A telecommunications company wants to analyze recorded customer support calls to identify recurring themes, customer pain points, and agent performance. Specifically, they need to determine *who* spoke *when* during the call, segmenting the audio by speaker (customer vs. agent). Which Azure AI Speech feature should the company use?
- AAzure AI Speech - Neural Text-to-Speech
- BAzure AI Speech - Custom Speech
- CAzure AI Speech - Speaker Diarization
- DAzure AI Speech - Speech-to-text (without speaker separation)
Show answer & explanationAnswer & explanation
Correct answer: C. Azure AI Speech - Speaker Diarization
Speaker Diarization is specifically designed to identify and segment different speakers in an audio recording, indicating who spoke when. This is crucial for analyzing multi-speaker conversations like customer support calls to differentiate between agent and customer utterances.
Why the other options are wrong
- A. Neural Text-to-Speech converts text to speech, which is unrelated to speaker identification.
- B. Custom Speech improves transcription accuracy, it doesn't identify different speakers.
- D. Standard Speech-to-text transcribes audio but typically doesn't separate or identify individual speakers in a multi-speaker conversation by default.
Azure AI Speech Speaker Diarization
A feature within Azure AI Speech that identifies and segments different speakers present in an audio recording, indicating 'who spoke when' without necessarily recognizing the specific identity of each speaker.
- Separates audio into speaker-specific segments.
- Assigns a unique ID to each detected speaker.
- Crucial for analyzing multi-party conversations (e.g., call center, meetings).
- Works in conjunction with speech-to-text to label speaker turns.
Memory trick: Listen to the talk, Know the voice, Mark the turn.