CLF-C02 Cloud Technology and Services Practice Question
Which AWS service enables automatic speech recognition (ASR) to convert audio from customer service calls into text for further analysis?
⚠ Common exam trap
A common mix-up: candidates confuse Amazon Lex (which also uses ASR) with Amazon Transcribe, but Lex's ASR is used for real-time conversational interactions, not for batch transcription of recorded audio for analysis.
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
✓
Amazon Transcribe
Amazon Transcribe is the correct AWS service for automatic speech recognition (ASR) because it is specifically designed to convert audio speech into text. It uses deep learning-based ASR models to process audio files or real-time streams, making it ideal for transcribing customer service call recordings for downstream analysis.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Amazon Polly
Why it's wrong here
Amazon Polly is a text-to-speech (TTS) service that synthesizes lifelike speech from plain text or SSML markup, generating audio files or streaming audio output. It is the reverse of what the scenario requires: it converts text into spoken words, not speech into text. Feeding call recordings to Polly would fail because the service expects text input, not audio. In short, Polly solves the opposite problem from the one stated.
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Amazon Lex
Why it's wrong here
Amazon Lex provides automatic speech recognition (ASR) and natural-language understanding (NLU) to build conversational interfaces such as chatbots and voice assistants. Although it does perform speech-to-text, it is engineered for real-time, interactive dialogue with bots and requires the configuration of intents, slots, and a bot infrastructure. It is not suited for offline batch transcription of pre-recorded call recordings into plain text documents. For large-scale transcription of stored audio, you need a purpose-built batch ASR service, not a conversational AI platform.
- ✓
Amazon Transcribe
Why this is correct
Amazon Transcribe is a machine-learning service purpose-built for automatic speech recognition (ASR), converting audio or video files containing speech into accurate text transcripts. It supports both batch processing for pre-recorded files stored in Amazon S3 and real-time streaming, and it includes features such as speaker diarization, custom vocabularies, language identification, and timestamp generation. This makes it the correct service to transcribe call recordings, as it directly turns the audio content into searchable, analyzable text. Its batch API can process large numbers of files asynchronously, matching common post-call analytics workflows.
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Amazon Comprehend
Why it's wrong here
Amazon Comprehend is a natural-language processing (NLP) service that extracts entities, key phrases, sentiment, and language from unstructured text. It cannot ingest audio or media files — it requires text as input and has no audio transcription capability. Therefore, while it could analyze the content of a transcript after it is produced, it cannot convert call recordings into text. Its job starts only after speech has already been transcribed.
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
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