AI-900 Question 25
Select 2A company wants to implement an AI solution that can analyze customer feedback from emails, categorize them based on sentiment (positive, neutral, or negative), and extract key topics mentioned in the text. Which natural language processing workloads are most appropriate for this scenario?
- A
Sentiment analysis
- B
Key phrase extraction
- C
Speech-to-text transcription
- D
Optical character recognition (OCR)
- E
Language translation
Show answer and explanation
Correct answers: A, B
Explanation
The scenario requires analyzing customer feedback in text form to categorize sentiment and extract key topics. Sentiment analysis and key phrase extraction are specific natural language processing (NLP) workloads that address these needs. Other options, such as speech-to-text, OCR, and translation, are unrelated to the requirements described in the scenario.
- A. Correct.
Sentiment analysis is used to determine the sentiment (positive, neutral, or negative) expressed in text, which is a key requirement in this scenario.
- B. Correct.
Key phrase extraction identifies significant topics or phrases in a block of text, which aligns with the need to extract key topics from customer feedback.
- C. Incorrect.
Speech-to-text transcription converts spoken language into written text, but the scenario involves analyzing textual data (emails), not spoken input.
- D. Incorrect.
Optical character recognition (OCR) is used to extract text from images or scanned documents, which is unrelated to the task of analyzing customer feedback from emails.
- E. Incorrect.
Language translation converts text from one language to another, but the scenario does not mention any need for translation services.