Q66 — AWS AIF-C01 Ch.2

Question 66 of 100 | ← Chapter 2

Select the correct machine learning technique from the list below to build a voice command recognition application. Which ML technique should be selected to train a model to recognize voice commands based on labeled audio data?

• A. Supervised Learning ✓
• B. Semi-supervised Learning
• C. Unsupervised Learning

Correct Answer: A. Supervised Learning

Explanation

A. Supervised Learning is the correct choice. Supervised learning trains models to recognize patterns in labeled data (e.g., audio clips annotated with corresponding commands) and make predictions on new inputs. Since the task requires training on labeled voice command data to recognize new commands, supervised learning is the appropriate technique. B. Semi-supervised learning combines limited labeled data with abundant unlabeled data—but here, a fully labeled dataset is available, making semi-supervision unnecessary. C. Unsupervised learning discovers hidden structures without labels—unsuitable for command recognition, which depends on explicit label supervision. Thus, supervised learning is optimal for leveraging labeled voice data to train accurate command recognition.