What happens after someone downloads a dataset from Mozilla Data Collective? For some AI builders, that data becomes part of a product already reaching users. For others, it plays an equally important role much earlier in development, helping them test an idea, improve a model or identify problems before a
Building AI that works for more people starts with the datasets behind it. But representation isn’t simply a matter of collecting more. It means thinking intentionally about who is represented, how those contributions are collected and whether builders have what they need to understand how their technology performs across
We've rolled out a change to rate limits on Mozilla Data Collective as part of expanding the types of accounts we offer. Starting today, new rate limits are in effect based on the type of account you have: * Free accounts have a rate limit of 7 dataset downloads
Our Python SDK client, which lets users interact with our platform through their Python environment, just got some exciting improvements! The headline is that dataset uploads through our client are now executed concurrently by default, which lets datasets land on the platform several times faster. Alongside that, over the past
Use your favourite LLM or agents to search the MDC data catalogue with our new MCP server
Scripted Speech v27 and Spontaneous Speech v5 are now live on the Mozilla Data Collective platform.
Lost In Transcription: Advancing Speech Recognition for Underserved Linguistic Contexts This competition evaluates performance on real-world bilingual dialogues in Indonesian-Javanese, Nahuatl-Spanish, and Spanish-English. For speech technologies to truly have an impact on the world, they must adapt to how people actually communicate in digitally-mediated settings.
Helping organisations participate more directly in the AI economy while making it easier for AI builders to discover responsibly sourced datasets. Earlier this month, we shared a preview of Compensated Datasets and our vision for creating more transparent ways for organisations to participate in the AI economy while retaining agency
Mozilla Common Voice is a massively multilingual platform for collecting speech data to train automatic speech recognition (ASR). Its mission is simple: to make language technology understand everyone’s mother tongue. But for datasets to be genuinely useful, they also need to be manageable. Many of the larger Common Voice
New collaboration expands visibility for community-governed language datasets and improves exploration of linguistic resources, services and tools. Mozilla Data Collective datasets are now discoverable through CLARIN’s Virtual Language Observatory, making it easier for researchers, developers and language technology practitioners in Europe to find multilingual and community-centered datasets
Mozilla Data Collective was built to redefine how AI data is created, shared, and governed. As part of our mission to be the data sharing platform for human agency and fair value exchange, we have long-teased what so many partners and community members have requested: a tangible way to
Why fine-tuning Whisper is a dataset problem OpenAI's Whisper changed what's possible in speech recognition: a single multilingual model with strong zero-shot performance across dozens of languages. But "dozens" is the catch. But for the long tail of the world's