3 articles tagged with #african-languages. AI-curated summaries with sentiment analysis and key takeaways from 50+ sources.
Researchers have released WAXAL, a large-scale multilingual speech dataset covering 24 Sub-Saharan African languages representing over 100 million speakers. The dataset includes 1,250 hours of transcribed speech for ASR and 235 hours of high-quality recordings for TTS, released under CC-BY-4.0 license to advance inclusive AI technologies.
Google AI has released WAXAL, an open multilingual speech dataset covering 24 African languages to improve Automatic Speech Recognition and Text-to-Speech systems. This addresses the significant data distribution problem where African languages remain poorly represented in speech technology training corpora.
Microsoft Research launched Paza, a human-centered speech recognition pipeline, and PazaBench, the first benchmark leaderboard specifically designed for low-resource languages. The initiative covers 39 African languages with 52 models and has been tested with real communities to improve AI accessibility for underrepresented languages.
