// Agent Transcript JSON

Give agents transcripts they can actually reason over.

Export agent-ready transcript JSON from audio and video. Include speaker turns, timestamps, chapters, summaries, quality warnings, and artifact links.

JSONschema
vocce · transcribe● live
点击或拖拽上传
上传音频或视频文件 · ≤ 50MB
// runs in your agent, ships to your stack Claude Code Cursor Gemini MCP CLI REST API n8n Zapier Make GitHub Actions Notion HubSpot
// runs in your agent, ships to your stack Claude Code Cursor Gemini MCP CLI REST API n8n Zapier Make GitHub Actions Notion HubSpot
// What you get

One upload. Every file the next step needs.

The same reliable Vocce pipeline, focused on this job. Free 3-minute preview, then pay only when the export matters.

Speaker turns
Timestamps
Chapters
Quality warnings
Artifact links
// How it works

How to get agent-ready transcript JSON

01
Upload or paste a URL Any format, any length — Vocce normalizes it.
02
One reliable call Clean, compress, transcribe, diarize, summarize.
03
Export the pack Transcript, subtitles, summary, and agent JSON.
// who uses agent transcript json

Built for real workflows.

RAG & search

Index speaker turns with timestamps instead of one giant text blob — retrieval gets precise.

Agent pipelines

Agents reason over structure: who said what, when, with what confidence — and chain follow-up actions.

Analytics

Mine calls and episodes for topics, decisions, and sentiment with a stable, versioned schema.

// faq

Agent Transcript JSON, answered.

What is agent transcript JSON? +

A structured, versioned transcript format (agent.v1): speaker turns with timestamps, chapters, summaries, quality warnings, and links to every artifact — designed for code and agents, not human reading.

Why not just plain text transcripts? +

Plain text loses who spoke, when, and how confident the recognition was. Structure is what lets an agent quote accurately, jump to moments, and decide next actions.

Is the schema stable? +

Yes — it's versioned (agent.v1) and identical across MCP, CLI, REST API, and automation nodes, so integrations don't silently break.

What about low-quality audio? +

Quality warnings are part of the schema: noise, overlap, and low-confidence segments are flagged so downstream logic can handle them explicitly.