What should you do?

You are an ML engineer in the contact center of a large enterprise. You need to build a sentiment analysis tool that predicts customer sentiment from recorded phone conversations. You need to identify the best approach to building a model while ensuring that the gender, age, and cultural differences of the customers who called the contact center do not impact any stage of the model development pipeline and results.

What should you do?
A . Extract sentiment directly from the voice recordings
B . Convert the speech to text and build a model based on the words
C . Convert the speech to text and extract sentiments based on the sentences
D . Convert the speech to text and extract sentiment using syntactical analysis

Answer: D

Explanation:

To ensure that gender, age, and cultural differences of the customers who called the contact center do not impact any stage of the model development pipeline and results, it is important to focus on the meaning and context of the conversation, rather than the characteristics of the speaker.

Converting the speech to text and then using syntactical analysis to extract sentiment will allow you to focus on the meaning and context of the conversation, rather than characteristics of the speaker. This approach will also give you more data to work with, as you can analyze the entire conversation, rather than just the voice recordings.

Reference: https://cloud.google.com/natural-language/docs/sentiment-tutorial