Introducing Universal-2: The latest advancement in Speech-to-Text technology. Capture the complexity of human speech, enhanced transcript quality, and better conversational insights by tapping into the next generation of Speech AI.
Five months ago, we introduced Universal-1, our best-in-class Speech-to-Text model that achieved remarkable robustness and accuracy across several industry-critical benchmarks. Today, we're launching Universal-2, which builds upon that foundation to address critical "last-mile" challenges in conversational data.
Universal-2 pushes the boundaries of Speech-to-Text technology by improving accuracy in areas that matter most for real-world applications:
⭐️ 24% improvement in the recognition of names, brands, locations, and more
⭐️ 21% increase in accuracy across critical data like phone numbers, zip codes, and other numerical identifiers
⭐️ 15% improvement in transcript structure with proper punctuation and casing for things like emails, dates, and dollar amounts
And most importantly, nearly 3/4s of users prefer Universal-2 over other Speech AI models.
Universal-2 bridges the gap between raw accuracy metrics and what makes transcripts truly useful—precise formatting, accurate proper nouns, and natural-looking output that businesses can trust.
Try it out and let us know what you're building with it!
Congratulations on the launch, @nick_morris4 and Team! Very cool name as well😉. STT model will only gain importance, and quality might be the main differentiator. Keep up the great work!
It's a great tool for keeping meeting minutes! And also helpful for university students :) Congrats on the launch!
Love your work @nick_morris4 but how does Universal-2 address privacy concerns especially when handling sensitive or confidential conversations?
The accuracy boost on proper nouns and numbers is a game-changer! 🎯 Been using Universal-1 for our customer call transcripts and those tricky company names and phone numbers were always a pain point. Just tested Universal-2 with some tough audio samples and wow - the difference in formatting and accuracy is night and day. Super impressed with how it handles those "last-mile" details that actually matter in real-world use. Worth the upgrade! 💪
Is it possible to read my knowledge base and extract some professional terminology keyword lists so that common terms in my industry or company can be targeted in subsequent speech material recognition?
