# 7.1 Data storage ### Data flow Currently, all [TWB Voice](#user-content-fn-1)[^1] users have to first sign up to TWB Platform. This is a platform that TWB developed for our community of linguists to use. They use it to take on translation jobs and for other language services too. Users have to accept the [terms and conditions](https://twbplatform.org/static/terms/) and [privacy policy](https://twbplatform.org/static/privacy/). Once they have agreed and signed up to TWB Platform, contributors can also log into TWB Voice. They can use the same login credentials (email and password). When they log in for the first time, they will need to accept some extra terms. These apply to the collection of voice data: * [Consent to participate in TWB Voice initiative](https://twbvoice.org/consent) * [Code of conduct](https://twbvoice.org/policy) New users will also have to provide some further information. This information is relevant to the collection of voice data: gender, year of birth, education level, and language variant. All of the data we collect is stored securely across multiple CLEAR Global databases. When they have done this, users can start doing TWB Voice tasks. The tasks they can do will depend on their level of access. ### Data segregation * We store personal information of users (name, email, gender, year of birth, education level, and language variant) separately from the user recordings. This means there is no risk that people could find out the identity of the speakers. * We only add the user metadata[^2] (gender, year of birth, education level, and language variant) to the recording when we export the data. We never share the user’s name or email in the published dataset[^3]. * We collect recordings for [Automatic Speech Recognition (ASR)](#user-content-fn-4)[^4] models through specific workflows. We store them in separate datasets from recordings for Text to Speech (TTS) models. We do this because we don’t publish TTS datasets fully, but use them internally to train models. We publish a partial set within the ASR dataset so that users can be anonymous. ### **Systems for storing and securing data** We store all voice recordings and metadata on secure servers. CLEAR Global manages and approves these servers. Our infrastructure ensures: * **user-based access control**, so access depends on the role of the user (e.g. reviewers, admins) * **strong password and device policies** are in place across all accounts * **data encryption** so that unauthorized persons cannot access or change the data * **automated and encrypted backups** on a regular schedule * **server hardening and monitoring** (firewall, operating system patches, minimal access configurations) * **event logging** to detect any unusual activity or misuse [^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]: **Metadata:** Extra information that gives some background to a dataset or parts of a dataset. Examples are demographics of the speakers (age, gender, accent), recording conditions (microphone type, level of background noise), or language-related details (dialect, speed of speaking, emotional tone). [^3]: **Dataset:** A collection of information that has been organized for use. A **voice dataset** is a collection of voice recordings (paired with transcription) with additional information (metadata) such as gender, age of the person recording to give more information on how the data set is constructed and to avoid bias. It is for use in research and for training or improving voice models. [^4]: **Automatic Speech Recognition (ASR) or Speech-to-Text (STT):** ASR converts spoken language into text. It can be used in voice assistants and transcription services, for example. You may hear both terms, ASR and STT, and they are almost the same. But STT can be a semi-manual process, while ASR is fully automated. ASR is like a smart listener that turns spoken words into written text on your device. While it does create the text automatically, it often needs some human input to make sure everything is correct, it can make mistakes especially in languages that are less used in the digital space. --- # Agent Instructions: Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter: ``` GET https://twbvoiceplaybook.clearglobal.org/7.-data-storage-compliance-and-ethical-issues/7.1-data-storage.md?ask= ``` The question should be specific, self-contained, and written in natural language. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.