Transcript Extraction

1. What is the primary purpose of the Azure AI Document Intelligence service in the context of transcript extraction?

To generate user reports To preprocess documents for OCR To convert scanned or PDF transcripts into structured data To store historical transcript data

2. Which of the following should NOT be a part of the normalization process for extracted transcript data?

Mapping letter grades to a canonical set Converting all units to a single system Creating a new institution entry upon detection Automatically changing course titles to uppercase

3. How should low-confidence fields in extracted transcripts be handled according to the lesson?

They can be ignored if they are insignificant They should be analyzed but not corrected They are marked as 'NeedsCorrection' for human review They should trigger an automated correction process

4. What aspect of the document extraction process requires a hybrid approach as mentioned in the lesson?

Using cloud services for storage Finding tables in transcripts and mapping them Normalizing grade formats Providing a UI for human corrections

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