Practice Test 4 | Google Cloud Certified Professional Data Engineer | Dumps | Mock Test
A mobile company has a requirement to scan the voice call and extract useful information from it. This is required for audit purposes. The information extracted needs to analyzed based on the sentiments. You as a data engineer is given a task to quickly deploy a solution and provide a feasibility report for the same. Choose the solution from the below option:
A. Create a machine learning model using a Tensorflow speech recognition API. This API will analyze the speech and fetch the sentiments out of it. Deploy this model on Google Cloud AI.
B. Create a machine learning model using Keras neural-network library. The API will analyze and fetch the sentiments. Deploy this model on Google Cloud API. Create a cloud function to send the voice input to this API and will receive corresponding output using online prediction.
C. Create a machine learning model using a Tensorflow speech recognition API. This API will analyze the speech and fetch the sentiments out of it. Deploy this model on Google Cloud AI. Create a cloud function to send the voice input to this API and will receive corresponding output using online prediction.
D. Deploy a Cloud Function that can save the voice recording to cloud storage. Deploy another cloud function that can transcribe the voice recording using Google Speech API and analyze using Google Natural Language API and save the result to cloud storage.
The correct answer is D.
Option A is incorrect. As the task of the data engineer is to quickly deploy the solution, creating a model using the TensorFlow speech recognition API will take a significant amount of time.
Option B is incorrect. Creating a model using Keras neural-network library will take a significant amount of time. As the solution needs to be delivered quickly and effectively, using Google managed API will offer lots of ease.
Option C is incorrect. As the task of the data engineer is to quickly deploy the solution, creating a model using the TensorFlow speech recognition API will take a significant amount of time.
Option D is correct. Using Cloud Speech Recognition and Natural Language API solution can be delivered quickly and with much accuracy. Google Natural Language API can analyze the content and fetch out the information based on the sentiments. Using the Cloud function the whole solution can be deployed easily and the results can be saved to cloud storage.
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