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A browser-based voice tutor prototype comes down to a few connected jobs: capture microphone audio, establish a secure realtime session, recognize when a learner has finished speaking, and play the tutor’s reply. The most direct route to natural conversation is a speech-to-speech Realtime session over WebRTC; a chained speech-to-text, text-agent, and text-to-speech design may fit better when you need to reuse an existing text agent or control each stage separately.
Ten days is a project constraint, not a proven delivery estimate. The implementation details below show how to plan the prototype and debug silence without mistaking a delayed transcript or an intentional wait for a broken microphone.
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Choose the voice architecture before building the interface
For a browser tutor that needs low-latency conversation, natural turn-taking, interruptions, and realtime tool calls, the official Realtime getting-started guide recommends a speech-to-speech approach. Its session maintains conversation state and can handle audio turns, tools, interruptions, and handoffs. The guide’s browser flow is an application server creating an ephemeral client credential, a frontend creating a RealtimeSession, and the browser connecting over WebRTC. See the Realtime guide.
A chained voice interface is also reasonable if you already have a text agent or need explicit control over recognition, reasoning, and speech generation as separate stages. The tradeoff is architectural: a single realtime session gives you integrated audio turns and interruption handling, while a chain can make each stage easier to inspect or reuse. Neither is the universal choice. OpenAI’s audio overview distinguishes the session-oriented Realtime path from voice interfaces built around an existing text agent.
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Do not mix snippets from different documentation interfaces casually. The reviewed documentation uses both “Realtime API” and newer “GPT-Live” naming in different guides; endpoint names, credentials, model identifiers, and event formats are not automatically interchangeable. Pick one current guide and follow its setup and event flow consistently. The Realtime guide also describes migration away from its beta interface, so older examples may have obsolete headers, setup steps, or event names.
Plan the ten-day build around working slices
Use the ten days as a way to limit scope, not as a promise that every developer can ship a polished tutor on that schedule. Keep the first version focused on a browser conversation loop; defer learning-outcome claims, student-data retention, and school deployment until those needs have been separately evaluated.
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Days 1–2: Prove the browser audio path
Start with a page that can request microphone access and establish the chosen browser connection on HTTPS or localhost. Confirm that the browser can receive and play remote audio before investing in tutor features. In the documented WebRTC setup, negotiated media tracks carry microphone input and generated speech, while a data channel carries JSON events such as transcripts and session updates. The WebRTC guide recommends WebRTC for browser voice applications; its lower-level flow has the browser create an SDP offer and a trusted application server exchange it with the API.
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Connect the session, give the tutor a narrowly defined role, and verify one cycle from spoken question to spoken answer. Keep the interaction simple enough to observe: a prompt, a response, and a visible state or event log. Avoid building a text transcript as if it were the audio transport; with WebRTC, media travels on tracks and the data channel provides session and event information.
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- YOUR AI PERSONAL ASSISTANT FOR EVERYDAY PRODUCTIVITY: More than a voice recorder, Pocket works as your AI personal assistant to capture, transcribe, and summarize meetings, calls, and ideas instantly. Core features are included out of the box, with optional advanced tools available for power users.
- ONE-TAP RECORDING FOR REAL-LIFE MOMENTS: Capture meetings, phone calls, and in-person conversations instantly with a simple tap, no typing, no interruptions, just effortless note-taking anywhere you go.
- SMART AI INSIGHTS & ORGANIZATION: Pocket automatically turns recordings into clear summaries, key action items and structured conversation maps so you can quickly review what matters without digging through audio.
- TURN CONVERSATIONS INTO ACTION WITH “ASK POCKET”: Don’t just record, understand. Instantly ask questions across your meetings, extract key insights and generate next steps in seconds. All grounded in your recordings, so answers stay accurate and reliable.
- MAGSAFE COMPATIBLE FOR SEAMLESS USE: Easily attach Pocket to your iPhone or other MagSafe compatible devices for convenient, hands-free recording on the go. Perfect for capturing meetings, calls, and ideas without needing to hold your device.
Days 6–8: Test interruptions, silence, and recovery
Try a learner interrupting the tutor, pausing mid-question, speaking with background noise, and restarting after a failed connection. The point is not to tune every edge case in the first pass, but to establish whether the system detects turns and whether silence is intentional or caused by a broken layer. Add clear on-screen states such as “connecting,” “listening,” and “speaking” so a quiet interface does not hide what the session is doing.
Days 9–10: Review security and document limits
Inspect the built browser bundle and server setup for exposed secrets. Write down the chosen API interface, its current session configuration, and known recovery steps so a future change does not accidentally combine incompatible examples. Do not describe the prototype as an effective educational intervention: the implementation sources establish how to build a voice interface, not whether it improves learning or suits a particular age group.
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- ONE-TAP RECORDING FOR REAL-LIFE MOMENTS: Capture meetings, phone calls, and in-person conversations instantly with a simple tap, no typing, no interruptions, just effortless note-taking anywhere you go.
- SMART AI INSIGHTS & ORGANIZATION: Pocket automatically turns recordings into clear summaries, key action items and structured conversation maps so you can quickly review what matters without digging through audio.
- TURN CONVERSATIONS INTO ACTION WITH “ASK POCKET”: Don’t just record, understand. Instantly ask questions across your meetings, extract key insights and generate next steps in seconds. All grounded in your recordings, so answers stay accurate and reliable.
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Connect the browser without exposing the project key
A standard project API key belongs on a trusted server, not in JavaScript shipped to users. The server can create an ephemeral client secret for the browser’s session, or, in the documented lower-level WebRTC flow, handle the SDP exchange itself. Keep the project key and session setup on the server; the browser receives only the credential or connection outcome appropriate to the chosen flow. A client bundle is visible to its users, so treating a project key as frontend configuration is a security mistake.
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- Prepare the page: serve it through HTTPS or localhost and request microphone permission from the browser.
- Establish the session: create the Realtime session in the frontend and connect through WebRTC, or use the server-mediated SDP flow described by the guide.
- Observe the two channels: verify the microphone and returned speech media tracks, then inspect data-channel session updates and events separately.
OpenAI’s WebRTC documentation recommends WebRTC rather than WebSockets for browser or mobile clients for more consistent performance. The audio overview points to WebSockets for server audio pipelines. Those transports imply different responsibilities: a browser WebRTC peer connection owns media transport, so do not assume generated audio must be manually reconstructed from data-channel events as it would be in a server-oriented audio pipeline.
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Diagnose “why is it silent?” one layer at a time
A tutor that does not speak may be deliberately waiting, or it may not have received or played audio. Check the path in order rather than changing the prompt first.
- Permission and origin: confirm the browser granted microphone access and the page is running on HTTPS or localhost, as required by the documented browser setup.
- Connection and session: confirm the peer connection completed and the session configuration was acknowledged. In the Agents SDK browser WebRTC guide, the initial session update is sent when the data channel opens; the SDK tries to wait for an acknowledgement before
connect()resolves, with a timeout fallback. A resolved connection is useful state, but inspect events and session state if behavior is still wrong. - Microphone track: verify that microphone capture succeeded and that an input media track was actually added to the connection. A permission prompt alone does not prove the session is sending audio.
- Turn detection and response: inspect whether voice activity detection (VAD) marked speech start or stop and whether a response was created. The Agents SDK voice guide explains that built-in VAD can determine when speech begins or ends and when to create a response.
- Transcript timing: do not treat a missing transcript at the instant a reply begins as proof the model heard nothing. Input transcription is asynchronous and can arrive after response generation has started; inspect event order and session state.
- Output playback: confirm that the remote audio track reaches an audio element and that playback is available in the browser. Check the browser’s audio output device and playback state, not only the data-channel log.
- Intentional waiting: if transport and turn detection look healthy, check whether the tutor prompt or a tool instructed it to stay quiet.
This sequence separates likely failure points; it is a practical debugging order, not a claim that every silent turn has the same cause. A headset with a microphone is optional for local testing. The documented setup requires microphone access and audio playback, not a particular accessory; a laptop microphone and speakers or other audio devices may work.
Make intentional silence different from a broken voice path
Voice agents can respond to silence, background noise, hold music, television, or side conversations unless their instructions account for those sounds. The Realtime prompting guide proposes a no-op tool such as wait_for_user for audio that is not addressed to the agent, paired with explicit instructions to stay quiet after using it. If a learner is clearly addressing the tutor but the words are unintelligible, the better behavior is to ask for clarification rather than silently wait.
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This distinction matters in a tutor: a quiet response can be a deliberate conversational choice, but a missing microphone track or unavailable playback is an engineering fault. Represent listening, waiting, and speaking as distinct interface states, and log session and event state so that the learner is not left guessing whether the tutor heard them.
Set boundaries for an educational prototype
The API and SDK implementation guidance supports building and debugging a voice interface. It does not establish student learning outcomes, tutoring efficacy, age appropriateness, educational inclusion, or compliance with privacy rules for student data. If the prototype is intended for schools or minors, or will store student audio, evaluate the relevant education and privacy requirements separately before deployment. Do not infer those assurances from a successful WebRTC call.
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