Paza: Introducing automatic speech recognition benchmarks and models for low resource languages

1. 1Develop and train speech recognition models for low-resource languages
2. 2Evaluate models using PazaBench, the first leaderboard for low-resource languages
3. 3Test models in real-world settings with communities to ensure practical applicability
4. 4Fine-tune models based on feedback and results from PazaBench and community testing

AI engineers, data scientists, and researchers working on natural language processing and speech recognition projects can benefit from Paza and PazaBench to improve their models and benchmark their performance

💡 Paza and PazaBench provide a much-needed platform for developing and evaluating speech recognition models for low-resource languages

🗣️ Paza introduces benchmarks & models for low-resource languages! 🌍 39 African languages & 52 models covered