# 7.3 Informed consent

### **Getting people’s consent**

The consent model uses a two-step method to get informed consent:

1. **Registration on TWB Platform:** Users agree to [standard terms](https://twbplatform.org/static/terms/) and [privacy policy](https://twbplatform.org/static/privacy/).
2. **TWB Voice onboarding:** Users have to accept the [TWB Voice](#user-content-fn-1)[^1] [Consent Form](https://twbvoice.org/consent). This explains:

* how we will use their [voice data](#user-content-fn-2)[^2]
* the review and quality control processes
* their rights to have data deleted and to take back consent

### **Quality review**

To ensure ethical use of the data and make sure it isn’t harmed or changed:

* Ask trained community reviewers or in-house [Language Leads](#user-content-fn-3)[^3] to check and approve each recording.
* Give reviewers clear criteria for approval or rejection. These should include clear audio, accurate language and compliance with the [Code of Conduct](https://twbvoice.org/policy). You can find more details in the [“Recording and Validation” section](/5.-recording-and-validation.md).
* If they find language that goes against the code of conduct, users can report it. We have clear processes to deal with these reports. We also explain what will happen if we confirm the abuse (data deletion, user suspended, etc.).

### **Rights and redress**

Contributors can contact CLEAR Global at any time to:

* ask to have their data deleted
* ask for information on downloads of their data
* make a complaint or ask for corrections if there is a breach of their rights under the GDPR.

<br>

[^1]: **TWB Voice:** A platform for collecting voice data. It was developed by CLEAR Global, who also own it. Users can make voice recordings to help with active data collection projects in TWB Voice by [signing up to the TWB Community](https://translatorswithoutborders.org/join-the-twb-community/). The main goal of TWB Voice is to help to develop voice technology for speakers of marginalized languages. For example, by creating the voice datasets that are needed to build language models for TTS and ASR.

[^2]: **Voice data:** Audio recordings of human speech. These recordings capture the acoustic features of spoken language, such as pronunciation, speaking patterns, and rhythm.

[^3]: **Language Leads (LLs):** Language experts with lots of experience. They can do spot checks to ensure quality and can give feedback.


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