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Capstone: Building Voice AI Android Apps

Project briefSelf-paced

The project

Build a voice note assistant with push-to-talk, transcript correction, interruptible playback and a text-only fallback.

Prerequisites

Complete the six teaching modules and their exercises. Keep the design notes and failure cases: they form the starting evidence for this project.

Build in increments

1. What a voice AI pipeline contains

Understand the responsibilities behind a spoken conversation. Apply the module decision to this project. Your checkpoint: You can name each latency and correctness boundary.

2. Capturing speech and detecting turns

Collect intentional input and preserve user control. Apply the module decision to this project. Your checkpoint: The user can always tell whether the app is recording.

3. Transcription and language understanding

Keep uncertain speech separate from confirmed intent. Apply the module decision to this project. Your checkpoint: An interim transcript cannot trigger a permanent action.

4. Speech synthesis and playback

Deliver understandable audio without losing application state. Apply the module decision to this project. Your checkpoint: Text and audio represent the same approved user-facing response.

5. Interruptions and conversation state

Handle overlapping speech without mixing turns. Apply the module decision to this project. Your checkpoint: No output from a superseded turn can re-enter active playback.

6. Latency, accessibility and reliability

Evaluate the entire voice experience under realistic conditions. Apply the module decision to this project. Your checkpoint: Your voice feature remains usable when speech input or output is unavailable.

Acceptance criteria

  • Display when the microphone is active
  • Measure capture-to-first-audio latency by pipeline stage
  • Stop stale speech on interruption and release audio resources

Evidence to submit

  • A repository or reproducible design artifact with setup instructions and tested tool versions.
  • A diagram showing components, data flow, authority and failure boundaries.
  • An evaluation table with inputs, expected results, actual results and explanations of failures.
  • A demonstration of the normal path and at least two relevant failure paths.
  • A short decision record covering alternatives, known limitations and the next improvement.

Review rubric

DimensionReady to demonstrateRevisit when
UnderstandingExplain each boundary and why it existsYou can only repeat framework terminology
ImplementationReproduce the core behavior from a clean setupHidden local state is required
ReliabilityShow bounded failures and useful recoveryThe demo only works on the happy path
EvidencePresent observed outcomes and limitationsSuccess is inferred from a generated answer
OwnershipModify a requirement and explain the consequencesYou cannot adapt the implementation independently

Do not treat a completed reading checklist as proof of project readiness. Revisit any module whose checkpoint you cannot demonstrate.

YOUR LEARNING JOURNEY

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Capstone: Building Voice AI Android Apps | Building Voice AI Android Apps | Android Engineers