Describe features of Natural Language Processing workloads on Azure →easyMultiple ChoiceObjective-mapped
AI-900 Practice Question: Describe features of Natural Language Processing workloads on Azure
What is 'text-to-speech' (TTS) in Azure AI Speech?
⚠ Common exam trap
Many candidates confuse text-to-speech with speech-to-text (option A) because both involve speech and text, but TTS is the reverse process of generating audio from text, not extracting text from audio.
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
✓
Converting written text into synthesised spoken audio
Text-to-speech (TTS) in Azure AI Speech converts written text into natural-sounding synthesized spoken audio. It uses deep neural networks to generate human-like speech from input text, enabling applications like voice assistants and audiobook narration.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Extracting text from speech audio recordings
Why it's wrong here
Extracting text from speech audio recordings is the task of automatic speech recognition (ASR) or speech-to-text, which processes acoustic signals, phonemes, and language models to produce a written transcript. Text-to-speech works in the opposite direction: it begins with written text and generates audio. This option is wrong because it misidentifies the direction of data flow and describes a separate Azure Speech service capability.
- ✓
Converting written text into synthesised spoken audio
Why this is correct
Converting written text into synthesized spoken audio is the core definition of text-to-speech (TTS). The system normalizes the input text, converts graphemes to phonemes, predicts prosody (pitch, duration, emphasis), and then generates a speech waveform using concatenative, parametric, or neural vocoders. This is exactly what TTS enables in voice assistants, audiobooks, screen readers, and other narration scenarios, making this the correct answer.
- ✗
Translating spoken text from one language to another in real time
Why it's wrong here
Real-time translation of spoken text from one language to another is a multi-stage pipeline that combines speech recognition, machine translation, and text-to-speech synthesis. While TTS may be the final stage that speaks the translated text aloud, TTS itself does not perform recognition or translation. The option incorrectly describes a full speech-to-speech translation system, which is not what TTS alone accomplishes.
- ✗
Detecting the emotional tone of speech audio to classify speaker sentiment
Why it's wrong here
Detecting emotional tone in speech audio to classify speaker sentiment is a speech emotion recognition or sentiment analysis task that operates on existing audio. It extracts acoustic features such as pitch, energy, speaking rate, and spectral characteristics to infer emotional labels. Text-to-speech synthesizes new audio output; it does not analyze or classify pre-recorded speech for emotional cues. Thus this option describes a different Azure AI capability rather than TTS.
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