Podcast QA before publish
Catch room echo, pacing dips, and inconsistent loudness before the episode goes live.
Is this take usable, and is that note in tune.
Not another voice generator. VoiceLab measures the take you already have: speech QA (noise floor, sibilance, room, pacing) and singing (pitch over time, where it drifted, vibrato and the range you held).
Analyse a voice sample for clarity, pacing, pause rhythm, room echo, clipping risk, and consistency across takes.
Mic capture and analysis stay in your browser. Nothing is uploaded.
How this is measured▸ Record a take or drop a file: speech QA above, singing pitch and vibrato below. Signed in? Results land in your Workspace. Your results land in your Workspace.
Also in VoiceLab
The tools above judge a speaking take. This one follows the note. Sing, and see where the pitch drifted, hear that exact stretch back, and get your vibrato and the range you held steadily.
VoiceLab is a voice quality analysis tool that runs entirely in your browser. It measures the things that actually decide whether a voice recording is usable: signal-to-noise ratio (how far the voice sits above the noise floor), sibilance energy (the harsh s and t sounds that fatigue listeners), room echo score (how much the room talks back), speech ratio and speaking rate, long silences, and clipping. Each metric comes back as a number, not a feeling, so two takes can be compared honestly.
That makes it a practical voice debugging tool: when a podcast take sounds off, the numbers say whether the problem is the room (echo score), the gain staging (clipping, noise floor), the mic distance (SNR), or the delivery (speaking rate, silences). The same checks work as a quality gate before speech-to-text, for judging TTS renders against a human reference, and for QA on meeting or call recordings.
Everything runs on-device via the WebAudio API: your audio is analyzed locally and never uploaded. When you need the same checks server-side or in an AI agent, the hosted API and MCP server expose this exact analysis as the analyze_voice tool, so a pipeline or agent can gate every render with the same numbers you see here.
Singing is a different question, so it has its own instrument below. It follows your pitch over time on a note grid and marks the stretches that stayed more than 25 cents out of tune for longer than a moment, which you can click to hear back. It also reports your vibrato rate and depth, and the range you actually held steady. One honest limit: without the melody it can tell you whether a note sits cleanly on a pitch, not whether it was the right note for the song. That distinction covers most of what singers mean by out of tune: drifting, scooping short, sitting between two notes.
Catch room echo, pacing dips, and inconsistent loudness before the episode goes live.
Flag pronunciation risks and pacing mismatches across language variants before dubbing finalises.
Keep tone, pace, and clarity coherent across 200 recorded modules from three voice actors.
We don’t generate voices. We make the voices you already have (yours, your hosts’, your hired talent’s) measurably better and more consistent.
Also in VoiceLab
Flag risky words against your target locale. Not built yet.
See what cleanup would do before you commit. Not built yet — VoiceLab measures, it never alters audio.
The demo above runs free, on your device.The lab above runs free, on your device. The same analysis is a hosted REST API and an MCP server, one key, EBU R128 / BS.1770-4 verified. VoiceLab exposes 2 endpoints / 2 MCP tools.
REST · POST
/v1/voicelab/qa speech-quality QA /v1/voicelab/segments speech segments MCP tools · https://audiolab.tools/mcp
Quick start
curl -X POST https://audiolab.tools/v1/voicelab/qa \
-H "Authorization: Bearer $AUDIOLAB_KEY" \
-H "content-type: application/json" \
-d '{"url":"https://your-audio.wav"}' Continue the workflow
Push the voice take to MixLab Analyzer for BS.1770-4 LUFS, true-peak, and tonal-balance verification.
Run the same voice file through HearLab to see how it would land for an assisted-listening audience.
For long-form material, let SignalLab auto-detect speech regions and timestamp them for editing.
Use CueLab to plan mic-routing, mix-minus, and recording paths for your show before going live.
SkillLab includes critical-listening drills that train the same dimensions VoiceLab QA scores.
MixLab, VoiceLab, and SignalLab hand audio off to one another without re-uploading. When you finish an analysis in one of those, the → Lab buttons in the demo chrome carry your decoded audio directly into the next lab’s analysis flow. The other labs open fresh.