PMLE Architecting Low-Code ML Solutions Practice Question
A media company wants to transcribe audio files from customer support calls into text for analysis. The audio is in English with clear speech and no background noise. They want a quick solution with no ML model training. Which Google Cloud service should they use?
⚠ Common exam trap
PMLE often tests the distinction between pre-trained APIs and custom training services; candidates may incorrectly assume that any ML task requires training a custom model, overlooking that Speech-to-Text API is a ready-to-use pre-trained service.
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
✓
Speech-to-Text API with the latest_long model
The Speech-to-Text API is Google Cloud's fully managed, pre-trained automatic speech recognition (ASR) service that requires no model training. The latest_long model is specifically optimized for transcribing long-form audio content such as customer support calls, providing high accuracy for clear English speech. Since the audio is clear with no background noise and the company wants a quick, training-free solution, Speech-to-Text API with latest_long is the ideal fit.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Translation API to translate the audio
Why it's wrong here
Translation API converts text between languages; it cannot decode audio at all, so no transcription occurs. It is tempting because it also handles English content, but it would only be correct after speech-to-text produced a transcript needing translation into another language.
- ✗
AutoML NLP to train a transcription model
Why it's wrong here
AutoML NLP trains custom text classification, entity extraction, or sentiment models; it does not perform speech-to-text. It is tempting because AutoML removes coding effort, but transcription needs Speech-to-Text, which handles English audio without any model training, so this option cannot produce transcripts.
- ✗
Vertex AI Workbench to train a custom speech recognition model
Why it's wrong here
Vertex AI Workbench is a notebook environment for building and training custom models, requiring ML development effort. It is tempting because custom training can tune accuracy, but the scenario demands no training, and Speech-to-Text already transcribes clear English audio without any model development.
- ✓
Speech-to-Text API with the latest_long model
Why this is correct
The latest_long model suits extended support-call audio, delivering accurate English transcription without any model training. It satisfies the stem's demand for a quick, pre-trained solution, unlike custom models requiring data and tuning. Speech-to-Text handles clear speech directly, so no ML expertise or training pipeline is needed.
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Written and reviewed by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
Last reviewed September 2026 · checked against the official Google Cloud exam blueprint
This PMLE 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 PMLE exam.