- A
Text-to-Speech API
Text-to-Speech API converts text into natural-sounding speech, supports low latency and custom voice models.
- B
Cloud Translation API
Why wrong: Cloud Translation API translates text between languages, not speech synthesis.
- C
Vertex AI Text Generation
Why wrong: Vertex AI Text Generation produces text output, not speech.
- D
Speech-to-Text API
Why wrong: Speech-to-Text API converts speech to text, not text to speech.
Question 714 of 997
Generative AI Leader Google AI Ecosystem and Strategy Practice Question
This Generative AI Leader practice question tests your understanding of google ai ecosystem and strategy. Read the scenario carefully and evaluate each option against the stated constraints before committing to an answer. After answering, compare your reasoning against the explanation and wrong-answer breakdown below. Once you have made your selection, read the full explanation to reinforce the concept and understand why each distractor is designed to mislead on exam day.
An enterprise needs to generate natural-sounding speech from text for a voice assistant. They require low latency and support for custom voice models. Which service should they use?
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Text-to-Speech API
The Text-to-Speech API (A) is correct because it is specifically designed to convert text into natural-sounding speech with low latency, and it supports custom voice models through features like Custom Voice and WaveNet voices. This directly meets the enterprise's requirements for a voice assistant that needs real-time, high-quality speech synthesis.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Text-to-Speech API
Why this is correct
Text-to-Speech API converts text into natural-sounding speech, supports low latency and custom voice models.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Cloud Translation API
Why it's wrong here
Cloud Translation API translates text between languages, not speech synthesis.
- ✗
Vertex AI Text Generation
Why it's wrong here
Vertex AI Text Generation produces text output, not speech.
- ✗
Speech-to-Text API
Why it's wrong here
Speech-to-Text API converts speech to text, not text to speech.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is confusing the Text-to-Speech API with the Speech-to-Text API, as candidates often mix up the direction of conversion (text-to-audio vs. audio-to-text) under time pressure.
Trap categories for this question
Command / output trap
Vertex AI Text Generation produces text output, not speech.
Detailed technical explanation
How to think about this question
The Text-to-Speech API leverages WaveNet or Google's custom neural network models to generate audio waveforms from text, achieving sub-200ms latency for real-time applications. Custom voice models are built using the Custom Voice feature, which requires a minimum of 1 hour of high-quality training data and supports SSML tags for fine-grained prosody control, such as pitch, rate, and volume adjustments.
KKey Concepts to Remember
- Read the scenario before looking for a memorised answer.
- Find the constraint that changes the correct option.
- Eliminate answers that are true in general but not in this case.
TExam Day Tips
- Watch for words such as best, first, most likely and least administrative effort.
- Review why wrong options are wrong, not only why the correct option is correct.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
How this comes up in practice
A cloud solutions architect for a retail company is evaluating services for a new workload. The correct answer here reflects best practice for the specific scenario described — not a general cloud recommendation. Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option. Cloud exam questions reward reading the constraint carefully: the same technology can be right or wrong depending on the use case.
What to study next
Got this wrong? Here's your next step.
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
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Google AI Ecosystem and Strategy — study guide chapter
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FAQ
Questions learners often ask
What does this Generative AI Leader question test?
Google AI Ecosystem and Strategy — This question tests Google AI Ecosystem and Strategy — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Text-to-Speech API — The Text-to-Speech API (A) is correct because it is specifically designed to convert text into natural-sounding speech with low latency, and it supports custom voice models through features like Custom Voice and WaveNet voices. This directly meets the enterprise's requirements for a voice assistant that needs real-time, high-quality speech synthesis.
What should I do if I get this Generative AI Leader question wrong?
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
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Last reviewed: Jul 4, 2026
This Generative AI Leader practice question is part of Courseiva's free Google Cloud certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the Generative AI Leader exam.
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