Which AI solution enables speech recognition and voice response for a mobile app?
A company is building a mobile app for users who have a visual impairment. The app must be able to hear what users say and provide voice responses. Which solution will meet these requirements?
Community Votes
100% of anonymous learners picked answer A. Votes are pick records left by other test-takers — they are not the verified answer.
Community Insight
The exam tests your ability to match AI use cases to the correct technology; the trap is choosing generative AI summarization, which can produce text but does not handle speech input.
For a mobile app that must hear user speech and provide voice responses, the correct AWS AIF-C01 answer is to use a deep learning neural network for speech recognition. Community consensus confirms this approach mirrors voice assistants like Alexa and Siri.
Choosing C (generative AI summarization) because it generates human-like text, but it does not convert spoken words to text or handle speech input, so it cannot satisfy the 'hear what users say' requirement.
Community Discussion (4 comments)
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Expert Analysis
Why the Answer Is Correct
A deep learning neural network is the core technology behind speech recognition systems. It converts spoken language into text, which can then be processed to generate a voice response, making option A the only choice that fully addresses both hearing and responding to users. Community comments note that this is similar to voice assistants like Amazon Alexa and Apple's Siri, which use deep learning for speech-to-text, processing, and text-to-speech. The comments also emphasize that option A directly handles the input of speech, unlike other options.Why the Other Options Are Wrong
Option B (build ML models to search for patterns in numeric data) is irrelevant because speech is audio, not numeric tabular data, and does not enable voice responses. Option C (generative AI summarization) can create human-like text but does not process audio input, so it fails the 'hear what users say' requirement. Option D (image classification and recognition) is for visual data, not speech, and would not help visually impaired users communicate via voice.Community Comment Notes
Comments unanimously support A. One commenter explicitly notes that while C sounds feasible, it does not handle the input of speeches. Another highlights the end-to-end architecture of voice assistants, reinforcing that deep learning covers both speech recognition and response generation. These insights align with the official AWS AIF-C01 objectives around identifying appropriate AI and ML solutions for different use cases.Official Reference
Exam Strategy
When a question involves voice or speech input, immediately think of speech recognition (deep learning) and text-to-speech services like Amazon Transcribe and Amazon Polly. Eliminate options that address visual, numeric, or text-only generation, as they cannot process spoken input.
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