Specify the experience
Define audiences, locales, accessibility needs, platform profiles, file formats, reading-speed rules, and acceptance criteria.
Subtitling, captioning, dubbing, audio description, and media QA designed as one accessible localization system.
We model the complete media path: source preparation, transcription, timing, translation, adaptation, recording, mixing, packaging, and player behavior.
Language and accessibility requirements are validated against the actual picture and audio, with separate treatment for subtitles, captions, SDH, dubbing, voice-over, and audio description.
We adapt the depth and sequence to your product or model stage, modalities, language scope, and internal team.
Define audiences, locales, accessibility needs, platform profiles, file formats, reading-speed rules, and acceptance criteria.
Transcribe, spot, translate, condense, adapt, record, and author sound and speaker cues against the media.
Run linguistic, temporal, visual, audio, accessibility, and technical QC in the delivery environment.
What the work means, where people and AI fit, how quality is judged, and what changes the estimate.
Subtitling, captioning, dubbing, audio description, and media QA designed as one accessible localization system. In practice, the work is bounded by a defined product or model decision, named audiences and locales, representative inputs, and acceptance criteria that can be reviewed.
Timed media fails when translation is separated from spotting, reading speed, speaker identity, sound cues, shot changes, dubbing constraints, and accessible delivery formats. The useful starting point is the smallest representative flow that can expose the cause, impact, and ownership of the problem.
Specify the experience: Define audiences, locales, accessibility needs, platform profiles, file formats, reading-speed rules, and acceptance criteria. Localize in time: Transcribe, spot, translate, condense, adapt, record, and author sound and speaker cues against the media. Conform and verify: Run linguistic, temporal, visual, audio, accessibility, and technical QC in the delivery environment.
The most useful inputs are representative source content or builds, target locales and audiences, brand and terminology guidance, release timing, known legal, safety, and and accessibility constraints. Admas can begin with a partial package, but missing context, rights, access, owners, or acceptance criteria will be made visible in the plan rather than treated as harmless assumptions.
Typical outputs include timed-text and accessibility specification, localized subtitle, caption, sdh, dubbing, or description assets, terminology and adaptation notes, and conformance and media-qc report. Deliverables are adapted to the team that must use them, with decisions, evidence, limitations, owners, and next actions made explicit.
Quality is measured against the real task and risk. Relevant evidence can include meaning and terminology accuracy, task completion in context, linguistic and functional defect severity, market acceptance, and rework and turnaround. Sampling, severity rules, reviewers, adjudication, and pass or fail thresholds should be agreed before the result is used as a release decision.
Automation can prepare files, pretranslate suitable content, enforce terminology, and flag mechanical defects. Translators, editors, market reviewers, localization engineers, testers, and program owners remain responsible for meaning, audience fit, product behavior, exceptions, and release decisions. The right allocation depends on consequence, content stability, available references, language coverage, reversibility, and the cost of a plausible but wrong result.
The estimate changes with word or asset volume, content type and risk, language pairs, workflow and file condition, review depth, turnaround, and engineering and project-management effort. Pricing should distinguish setup and discovery, repeatable units, specialist or engineering time, independent review, management, and external costs. A low unit price is not comparable if it excludes the QA cycle or shifts rework back to the buyer.
Tell us what you are building, which modalities and languages matter, and where progress is blocked.
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