Exam AWS Certified Solutions Architect - Associate SAA-C03 topic 1 question 199 discussion

The correct answer is B: Use Amazon Transcribe for multiple speaker recognition. Use Amazon Athena for transcript file analysis. Amazon Transcribe is a service that automatically transcribes spoken language into written text. It can handle multiple speakers and can generate transcript files in real-time or asynchronously. These transcript files can be stored in Amazon S3 for long-term storage. Amazon Athena is a query service that allows you to analyze data stored in Amazon S3 using SQL. You can use it to analyze the transcript files and identify patterns in the data. Option A is incorrect because Amazon Rekognition is a service for analyzing images and videos, not transcribing spoken language. Option C is incorrect because Amazon Translate is a service for translating text from one language to another, not transcribing spoken language. Option D is incorrect because Amazon Textract is a service for extracting text and data from documents and images, not transcribing spoken language.

This is a poorly worded question with poorly worded options. Rekognition and Translate cannot convert speech to text so those options A, C & D are gone. B is the closes option but it does not mention S3 or retention policy of 7 years. Just a best guess on massive assumptions.

Transcribe for speech to text conversion and Athena for analysis.

Option B is the most relevant one, but it doesn't mention how to retain data in 7 years...

check out this blog here: https://aws.amazon.com/de/blogs/machine-learning/automating-the-analysis-of-multi-speaker-audio-files-using-amazon-transcribe-and-amazon-athena/

Perfectly explained here: https://aws.amazon.com/de/blogs/machine-learning/automating-the-analysis-of-multi-speaker-audio-files-using-amazon-transcribe-and-amazon-athena/

really hope I could have this kind of question during the exam, 4 different techs in the first 5 words of the answer! Just go with the correct one and ignore the rest of the text XDDD

https://aws.amazon.com/blogs/machine-learning/automating-the-analysis-of-multi-speaker-audio-files-using-amazon-transcribe-and-amazon-athena/

Amazon Rekognition is primarily designed for image and video analysis, not for transcribing audio or recognizing multiple speakers. -> Option A and D are ruled out Amazon Translate is used for language translation -> Option C is ruled out

Provide multiple speaker recognition and generate transcript files = Amazon Transcribe Query the transcript files = Amazon Athena

The correct answer is B: Use Amazon Transcribe for multiple speaker recognition. Use Amazon Athena for transcript file analysis.

Tricky or incomplete question.. B is the answer because Transcribe is the right service for processing voice calls. But 7 years of storage is not covered (should add S3 storage) And Athena querying is just SQL querying, it cannot help you much to recognize business patterns, for that I would think some text analysis service like Comprehend would be needed. Unless... We use Transcribe not only to transcribe, but also to recognize some key words, and then create a DB/S3 record with multiple fields, e.g. if it is a telemarketing questionnaire, record answer for each question. Then SQL querying might be useful.

Transcribe and (s3) + Athena is the way to go here. Redshift sounds like an overkill

Amazon Transcribe provides accurate transcription of audio recordings with multiple speakers, generating transcript files. These files can be stored in Amazon S3. To analyze the transcripts and extract insights, Amazon Athena allows SQL-based querying of the stored files. A. Amazon Rekognition is for image and video analysis, not audio transcription. C. Amazon Translate is for language translation, not speaker recognition or transcript analysis. Amazon Redshift may not be the best choice for storing and querying transcript files. D. Amazon Rekognition is for image and video analysis, and Amazon Textract is for document extraction, not suitable for audio transcription or analysis. Storing the transcript files in S3 is appropriate, but the analysis requires a different service like Amazon Athena.

the solution that meets these requirements is option B.

B is correct

Amazon Transcribe is a service that convert speech into text, so B is the answer