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Echo9 generates broadcast-ready subtitles across every target language in a single pass then gives your team frame-level control and line-by-line human review, so quality is something you can measure, not something you hope for.
Trustworthy by design
Episodic content ships continuously. The old options force a trade-off between speed and proof. Echo9 removes it.
Inside the Subtitle Studio
Three synchronized areas: transcription and translation side by side, a live preview, and a frame-level timeline — so editors spend time on judgment, not on hunting for context.
Read the original and the localized line together, with surrounding dialogue for context. Edit the source and the change flows downstream to every target language. never the other way, so your transcript stays clean.
The review box shows about a minute of lines. Five dialogues, five lines, nothing more. Reviewers stay focused, move faster, and catch more, instead of drowning in a full episode at once.
Drag, trim, split and merge dialogue against the audio waveform down to the millisecond. 00:07:16:007. Add a missing line by drawing it on the ruler; the preview updates as you go.
Name speakers by gender and character F_Elena, M_David then bulk-apply across every line a character speaks. Rename once, update all fifty dialogues at once.
Work is structured by shows, seasons and episodes not a pile of loose files. Each episode has its own status, metadata and assignee; episodes run in parallel with clear ownership instead of sequential handoffs. Add a new episode to a project and it inherits the same target languages automatically.
Quality you can prove
Echo9 draws a hard line between what AI generated and what a human signed off on so "broadcast-safe" stops being a guess.
AI produces the first-pass subtitles for every selected language. The episode is drafted, timed and diarized — but not yet trusted for delivery.
Every line is ticked by a reviewer. An episode is only Completed when each dialogue is confirmed, and a project only when every episode is done.
Reviewers log errors across diarization, translation, split/merge and timing each category weighted. Add the count and the timestamp; Echo9 computes the score. Quality becomes evidence you can hand to a client, not an opinion.
Reviewers adapt for the audience, not the dictionary. An idiom like "driving me up the wall" gets carried over as the local expression for frustration rather than translated word for word the kind of judgment AI alone misses and audiences immediately notice.
How it flows
Create a project, add an episode, choose every target language in one go.
Auto-subtitles, timing and diarization generate across all languages roughly 30 minutes for a 40-minute episode.
Editors work the timeline and the one-minute box, tick each line, and log QA as they go.
Mark Completed and export delivery-ready SRT or VTT for downstream systems.
Delivery
Draft and final are never confused. Export AI-generated and human-reviewed versions separately, in the formats downstream systems expect.