Case Study : Scaling Audio Annotation across 40 languages
Written By Jiten Madia • Last Update Aug 28, 2026
Client context and challenge
A global AI data annotation platform and service that supports large-scale AI and data projects across markets and languages needed audio annotation capacity across multiple languages, requiring a large linguist network that could be mobilized quickly. Large-scale audio annotation projects can require substantial linguistic capacity across multiple markets, simultaneously. For this project, the requirement was to deliver 100 hours of audio annotation across 40 languages.
Our Approach
Meeting these requirements meant having access to linguists with the relevant language capabilities; and being able to bring them onto the project quickly. The scale of the requirements also meant that relying on a small pool of linguists would not suffice. The client needed access to a broader network that could support the volume and language coverage required for AI and data collection work. The key challenge was therefore scale and speed: bringing together enough linguists across a wide language footprint, without a long onboarding process. myTranscriptionPlace used its established linguist network to build the capacity required for the project.
A network built for multilingual projects
343 linguists covering 40 languages were identified, from myTranscriptionPlace's network. This gave the project access to a broad pool of language expertise rather than requiring linguists to be sourced individually for each language requirement.
Rapid onboarding
For large-scale annotation projects, the average working capacity of a single linguist in the network is 32 hours per week. The project required rapid mobilization, so onboarding speed was a critical part of the workflow. myTranscriptionPlace was able to onboard 300+ freelancers in an average of 1.5 days. This meant the required linguist capacity could be brought together quickly, without a prolonged ramp-up period.
Experience across AI and data projects
The team supported 15+ AI and data collection projects, gained experience in working with the scale and language requirements of this type of work. Rather than building a linguist pool from scratch for each new project, the current linguist network provided a ready base of language talent that was mobilized as requirements arose.
Results
The project demonstrated the ability to combine scale, language coverage and rapid onboarding for audio annotation.
100 hours of audio annotation delivered
343 linguists in the network
40 languages covered
300+ freelancers onboarded in an average of 1.5 days
32 hours/week average working capacity per linguist for large-scale annotation projects
