Ta-da Launches Enhanced Audio Tasks with French Support and Flexible Sessions
Ta-da Launches Enhanced Audio Tasks with French Support and Flexible Sessions
🎤 Voice tasks upgraded
Ta-da has upgraded its audio task platform with significant improvements for voice dataset creation.
New language support includes:
- French language tasks
- Native English recordings
- Non-native accent collection
Platform improvements feature:
- Revamped user interface
- Smoother task flow
- Flexible session lengths (10 seconds to 10 minutes)
- Mobile-friendly design
The platform helps train AI by collecting human voice data through simple prompt reading tasks. Users earn rewards for contributing to high-quality voice datasets that improve AI speech recognition.
Limited weekly collection slots are available, with spots filling quickly as demand grows.
🌍 New audio tasks are live on Ta-da. Just read simple prompts aloud in your language (English, French, and way more to come). Help build high-quality voice datasets for AI through quick human-in-the-loop contributions. Open to all, rewarding, and ready now. Your voice makes
AI agents like those from OpenAI’s AgentKit need human input to stay accurate. That’s where Ta-da’s HITL shines: read prompts in languages like English, Spanish, or French to build high-quality voice datasets. It’s how we train smarter AI! Dive in: app.ta-da.io
🌅 Sunday scroll: AI's exploding: OpenAI's AgentKit just dropped tools to ship agents faster, EU's pumping €1.3B into infra for tech sovereignty, and Deloitte says AI investments fueled 46% of US GDP growth this year. Wild times! But what's powering it all? High-quality
As promised, audio tasks just got a glow-up! Now in French, native English & non-native accents! Revamped UI, smoother flow, and sessions on the go: 10 seconds or 10 minutes, your call. Train AI that speaks like real humans, anywhere, anytime. Limited amount of audio collected
gm, new audio tasks dropping tomorrow, get your voice warmed up!
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**Multimodal AI is exploding** with a $63B generative AI market expected by end of year. These systems combine text, voice, and vision capabilities. **The challenge:** AI models need diverse, human-grounded datasets to eliminate biases and reduce hallucinations. **Crowdsourcing emerges as solution:** - Human contributors provide accents, audio clips, and labels - Creates more ethical, globally representative training data - Enables AI that adapts rather than assumes **The opportunity:** Building AI systems that truly understand the world requires human input across languages, cultures, and contexts. This represents a shift toward more inclusive AI development where human diversity becomes a competitive advantage.
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