A city council wants live captions displayed on a screen during public meetings as officials speak, so attendees who are deaf or hard of hearing can follow the discussion in real time. Which AI capability should the team implement?
Select an answer to reveal the explanation.
Short Explanation
The council isn't trying to figure out what officials mean or translate anything into another language, they just need what's being said out loud to show up as words on a screen, as it's being said. That's a straightforward audio-to-text job. Turning text into spoken audio would run in exactly the wrong direction, since the audio already exists and it's the text that's missing. And figuring out the intent behind a sentence, like whether it's a complaint or a request, doesn't produce readable captions at all, it just labels what a sentence is trying to do. What this room full of attendees actually needs is a live transcript of the spoken words themselves, generated the moment they're spoken, so anyone who can't hear the meeting can still follow along by reading.
Full Explanation
The correct answer is C. Speech-to-text, also called speech recognition, converts spoken audio into written text in real time, which is exactly what is needed to display live captions as officials speak during the meeting. Option A is incorrect because text-to-speech does the opposite of what is needed here: it converts written text into spoken audio, which would not help attendees who need to read captions of speech that is already being spoken aloud. Option B is incorrect because text translation converts written or spoken content from one language into another; nothing in the scenario indicates officials are speaking a different language than the audience needs, so translation is not the missing capability, and even if it were added later it would still require speech-to-text as the first step to produce text from the audio. Option D is incorrect because intent recognition analyzes text to determine what action or goal a speaker or writer is expressing, such as identifying that a customer message is a complaint, which is unrelated to producing a readable, real-time transcript of spoken words on a screen. The council's core need is turning spoken audio into on-screen text as it happens, which is the defining function of speech recognition.