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Overview

Translation takes your transcribed captions and produces natural, spoken-register captions in your target languages. Unlike literal machine translation, Neolli’s pipeline is specifically tuned for video captions — it accounts for sentence boundaries, speaker context, timing constraints, and language-specific patterns.

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Adding languages

  1. From the video workspace, click Add Languages
  2. Select target languages from the grid, or use a preset (Top 3, Top 5, Top 10)
  3. Choose whether to generate captions, dubbing, or both
  4. Click Start
Add Languages wizard with language grid and presets
Language presets select the most popular YouTube audience languages by reach. Top 3 covers ~60% of global YouTube viewers, Top 10 covers ~85%.

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Supported languages

Neolli supports translation into 30 languages. See Supported Languages for the full matrix with transcription and dubbing availability.

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How translation works

Neolli uses a multi-pass AI translation pipeline to balance accuracy, timing, and natural speech:
For caption translation, the pipeline:
  1. Translates — Groups related segments and translates them as complete thoughts, maintaining speaker context and continuity
  2. Condenses — Shortens any segments that exceed their available display time while keeping captions natural and readable
  3. Polishes — Fixes language-specific issues like missing subjects, unnatural word order, or awkward phrasing
Each language has dedicated guidance to ensure translations sound natural and spoken, not robotic or literal.

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Metadata translation

When you translate a video, Neolli also translates the video’s title and description into each target language. This is especially useful when pushing to YouTube, where localized metadata helps international discoverability.

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Editing translations

After translation completes, you can edit any segment in the caption editor. Changes are saved as a new version — you can switch between the AI-generated original and your edits at any time.

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Credit cost

Translation is charged at 31 credits per 1,000 characters of source text, per language. A typical 10-minute video contains roughly 7,500 characters of speech. See Credit Costs for a detailed breakdown.