3.3 Building your team
The size of your team and the roles you need for a project to collect will depend on your project’s aims, context, and available resources. are at the center. They make recordings, check the quality of the data, and give feedback to the team and to other contributors, so they should be involved in shaping the project from the start.
Here are the key roles and typical responsibilities of a project team that helps community members to contribute with their voices:
Community engagement lead: supports contributors, organizes training, creates guidance materials, and collects and responds to feedback.
Language expert: helps edit or develop the available texts, advises on dialect and linguistic features, and helps with translation or content for the community. Note: not all voice contributors are linguists, and not all linguists will want to make recordings. These can be two distinct roles.
NLP specialist: makes sure that the data meets quality standards for its intended use, from defining scope through to publication.
Technical lead/engineers: maintains the data collection platform, deals with technical issues, and makes sure that data is handled and stored securely.
Data protection specialist: takes care of privacy, processes for informed consent, and ethical data use.
Project coordinator: manages timelines and budgets, and makes sure there is good communication between team members.
Three core teams supported CLEAR Global’s projects:
Community team, including:
Community Lead: Designed and led the strategy for community engagement, organized feedback surveys, and ran a contributor . This role helped us to identify the difference between shared challenges and challenges specific to a language.
(Hausa, Kanuri, Shuwa Arabic): Each language had a lead who helped with linguistic tasks, checked the quality of contributions, and kept up direct communication with their community.
Technical team, including:
a computational linguist who helped design prompts, advised on quality guidelines for data collection, checked data quality at regular intervals during data collection, and helped with processing and publication of the datasets.
platform developers who maintained the TWB Voice recording platform and dealt with technical issues that users reported during data collection.
Data Protection Lead to ensure compliance with data protection standards, including
Project coordination team, including:
two project managers: one to oversee the overall project timeline (from defining the scope to dataset publication), and a second to focus on daily tasks in the active data collection projects and contributor support.
a Monitoring, Evaluation, Accountability, and Learning (MEAL) specialist who designed feedback mechanisms, a monitoring framework, and a learning review to inform future projects.
There were also some supporting roles, including finance, HR, logistics and a communications specialist. Most of the work was done remotely. Team leads met every two weeks, and sub-teams more often to manage daily tasks. Slack, a platform for team communication, was used for quick updates and to track issues, especially for resolving tech problems quickly.
Key learnings on team structure from the pilot projects:
Combine or split roles based on capacity. With smaller teams, one person could take on more than one role—for example, a data protection lead could also help with project management, or a Language Lead may also manage community engagement.
Focus on critical functions beyond the set roles and responsibilities. For example, we used tools like Whatsapp for communication. This meant that multiple team members had to monitor and help with communications in those channels. It was also helpful that several people understood the structure of the TWB Voice platform. This helped avoid delays when the main team member was not available.
The workload of the Language Lead varied a lot, and sometimes they had too much work. In future projects, we would try to separate community engagement from linguistic tasks. We would also train contributors to help with activities like collecting and organizing the voice recordings. This would help to avoid bottlenecks.
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