Microsoft Certified: Azure AI Engineer AssociateImplement natural language processing solutionsMedium
A contact center is planning to implement an AI solution to analyze customer call recordings. The goal is to automatically identify and extract key phrases and topics discussed during each call to improve agent training and identify common customer issues. Which Azure AI Language feature is best suited for this task?
- AText Summarization
- BNamed Entity Recognition (NER)
- CSentiment Analysis
- DKey Phrase Extraction
Show answer & explanationAnswer & explanation
Correct answer: D. Key Phrase Extraction
Key Phrase Extraction is designed to identify the main points and topics from unstructured text, which is ideal for summarizing the essence of customer calls and identifying recurring themes. While other options are NLP features, they don't directly fulfill the requirement of identifying 'key phrases and topics'.
Why the other options are wrong
- A. Text Summarization condenses the text into a shorter version, which is different from extracting specific key phrases.
- B. NER identifies and categorizes specific entities (people, places, organizations) but not overarching key phrases or topics.
- C. Sentiment Analysis determines the emotional tone but not the specific topics.
Key Phrase Extraction
An Azure AI Language feature that identifies and extracts the main concepts or topics from unstructured text, helping to quickly understand the content's essence.
- Returns a list of strings denoting the key talking points.
- Works well for identifying themes in large volumes of text.
- Can be used for content indexing, topic modeling, and search.
Memory trick: Analyze text for feelings, names, and key ideas.