Microsoft Certified: Azure AI Engineer AssociateImplement natural language processing solutionsMedium
A telecommunications company wants to analyze recorded customer support calls to identify patterns in customer complaints and agent performance. The audio recordings often contain multiple speakers (customer and agent) talking over each other or at different times. The company needs to accurately identify who said what in the transcript. Which Azure AI Speech feature is essential for this requirement?
- AText-to-Speech synthesis.
- BSpeech-to-Text with language identification.
- CSpeaker Diarization.
- DCustom Speech model adaptation.
Show answer & explanationAnswer & explanation
Correct answer: C. Speaker Diarization.
The requirement to 'accurately identify who said what in the transcript' when 'multiple speakers (customer and agent) talking over each other or at different times' directly points to Speaker Diarization. This feature separates an audio stream into segments by speaker, allowing for speaker attribution in the transcript.
Why the other options are wrong
- A. Text-to-Speech synthesizes audio from text, which is the opposite of the requirement.
- B. Speech-to-Text transcribes audio to text but doesn't differentiate between speakers.
- D. Custom Speech improves transcription accuracy for specific domains or acoustics, but not speaker separation.
Speaker Diarization
A feature of Azure AI Speech that identifies and labels different speakers in an audio recording, indicating 'who spoke when' in the transcript.
- Separates audio into segments based on speaker identity.
- Assigns labels (e.g., Speaker 1, Speaker 2) to each segment.
- Crucial for transcribing multi-person conversations and meetings.
Memory trick: Diarization Divides Dialogue by speaker.