A media company is building an automated metadata archiving pipeline for its catalog of Spanish-language news broadcasts. The pipeline must perform the following tasks:
1. Convert the spoken Spanish audio of the broadcasts into written Spanish text.
2. Translate the generated Spanish text into English text.
3. Analyze the video frames to detect and extract on-screen news banners (text) and identify prominent public figures or brand logos.
To minimize custom machine learning model development, the company wants to use pre-trained AWS AI services. Which combination of AWS services should the company use to meet these requirements?
- Amazon Transcribe to convert the spoken audio to text, Amazon Translate to translate the text, and Amazon Rekognition to extract text and identify public figures from the video framesAnswer
- BAmazon Polly to convert the spoken audio to text, Amazon Comprehend to translate the text, and Amazon Rekognition to extract text and identify public figures from the video frames
- CAmazon Transcribe to convert the spoken audio to text, Amazon Translate to translate the text, and Amazon SageMaker to build custom models to extract text and identify public figures from the video frames
- DAmazon Lex to convert the spoken audio to text, Amazon Translate to translate the text, and Amazon Rekognition to extract text and identify public figures from the video frames
Answer
The combination of Amazon Transcribe to convert the spoken audio to text, Amazon Translate to translate the text, and Amazon Rekognition to extract text and identify public figures from the video frames.
The correct option correctly maps each task to the corresponding fully managed, pre-trained AWS AI service: Amazon Transcribe converts the spoken Spanish audio to text, Amazon Translate translates the Spanish text into English, and Amazon Rekognition extracts on-screen text and identifies public figures from the video frames.
Step-by-Step Solution
Key Concept
AWS Machine Learning Services
Estimated Time:2m 0s