Preparing Practice Exam…
Please wait a moment while the system generates the exam questions, answers, and study session.
Please wait a moment while the system generates the exam questions, answers, and study session.
Google Cloud Certified Professional Machine Learning Engineer · Google Cloud
Select one answer.
Written by other learners. Comments can disagree with the marked answer — check the official documentation when in doubt.
The key requirement is: ensure that gender, age, and cultural differences do not impact the model development pipeline and results. Voice recordings contain many sensitive and potentially bias-inducing attributes: gender, age, accent, speaking style, emotional tone, cultural background. To minimize bias, the best approach is to: convert speech to text, build sentiment analysis from textual content only. Using text reduces reliance on sensitive vocal characteristics while still capturing sentiment meaning effectively.
goes a step further by analyzing the structure and grammatical relationships within the sentences. This approach abstracts away from just the words used and focuses on how the words are put together, capturing deeper semantic and contextual information, less likely to be influenced by demographic variations in language use
A. Convert speech to text and extract sentiments based on sentences: This method focuses on the content of the conversation, minimizing the influence of factors like voice tone (which can be culturally or gender-specific). Sentiment analysis techniques can analyze the meaning and context of sentences to identify positive, negative, or neutral sentiment.