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Your company stores a large number of audio files of phone calls made to your...

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Your company stores a large number of audio files of phone calls made to your customer call center in an on-premises database. Each audio file is in wav format and is approximately 5 minutes long. You need to analyze these audio files for customer sentiment. You plan to use the Speech-to-Text API. You want to use the most efficient approach. What should you do?

A.

1 Upload the audio files to Cloud Storage

2. Call the speech: Iongrunningrecognize API endpoint to generate transcriptions

3. Call the predict method of an AutoML sentiment analysis model to analyze the transcriptions

B.

1 Upload the audio files to Cloud Storage

2 Call the speech: Iongrunningrecognize API endpoint to generate transcriptions.

3 Create a Cloud Function that calls the Natural Language API by using the analyzesentiment method

C.

1 Iterate over your local Tiles in Python

2. Use the Speech-to-Text Python library to create a speech.RecognitionAudio object and set the content to the audio file data

3. Call the speech: recognize API endpoint to generate transcriptions

4. Call the predict method of an AutoML sentiment analysis model to analyze the transcriptions

D.

1 Iterate over your local files in Python

2 Use the Speech-to-Text Python Library to create a speech.RecognitionAudio object, and set the content to the audio file data

3. Call the speech: lengrunningrecognize API endpoint to generate transcriptions

4 Call the Natural Language API by using the analyzesenriment method

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