---
type: "Evidence Item"
title: "How Descript engineers multilingual video dubbing at scale"
description: "Using OpenAI reasoning models, Descript unlocked automatic localization of large content libraries without losing timing or meaning."
resource: "https://openai.com/index/descript"
tags: ["appendix-iii", "benchmark", "openai"]
timestamp: "2026-03-06"
category: "benchmark"
publisher: "OpenAI"
cope_score: 76
confidence: 0.9
---

# How Descript engineers multilingual video dubbing at scale

# Claim

Using OpenAI reasoning models, Descript unlocked automatic localization of large content libraries without losing timing or meaning.

# Relevance

Appendix III, section one: model and benchmark capability evidence

# Oracle Verdict

This belongs in the register because benchmark and model-release claims set the ceiling for the next wave of deployment stories. The labour-market effect is indirect today, but it becomes direct when these gains are packaged into agents, APIs, and enterprise tools.

# Metadata

* Publisher: OpenAI
* Category: benchmark
* Sector: Media and content
* Capability: Multimodal content generation and media workflows
* Cope score: 76
* Confidence: 0.9

# Related Concepts

* [Live evidence index](index.md)
* [Thesis](../thesis.md)

# Citations

[1] [How Descript engineers multilingual video dubbing at scale](https://openai.com/index/descript)