AssemblyAI
Transform speech into meaning with one robust API
4.8•32 reviews•5.6K followers
Transform speech into meaning with one robust API
4.8•32 reviews•5.6K followers
Build new AI products with voice data leveraging AssemblyAI’s industry-leading Speech AI models for accurate speech-to-text, speaker detection, sentiment analysis, chapter detection, PII redaction, and more.
Join 5,000+ industry-leading companies—including Fireflies.ai, Glean, and Loop—unlocking the power of voice data and launching best-in-class products and experiences.
AssemblyAI
LanguaTalk
@devon_malloy congrats on the launch. Couple of Qs: 1) which languages does it support? 2) do you have benchmark data by language vs 11labs Scribe and Deepgram Nova-3? Couldn't find answers to either.
AssemblyAI
@alex_redfern The Universal-Streaming model is currently available in english. As for the benchmark data, we have a robust breakdown on the comparison for Nova-3. A few impacts worth noting is the 44% increase in P50 Latency, 66% reduction in cost, and 21% better WER for alphanumerics. I will pass on the feedback for a Scribe benchmark. Thanks!
Pokecut
🚀 AssemblyAI is a total game-changer for anyone building AI products with voice data! Their speech-to-text accuracy is seriously impressive, and the extra features like speaker detection, sentiment analysis, and chapter detection make it super powerful. 🗣️✨
I especially love the PII redaction—privacy is a huge concern, and AssemblyAI handles it seamlessly. Knowing top companies like Fireflies.ai and Glean trust this platform gives me a lot of confidence, too! 💪
If you’re looking to unlock the true potential of voice data for your product, AssemblyAI is a must-try. Excited to see how it keeps evolving! 🔥
Hey, AssemblyAI Team,
I’ve been working on a fully offline, on-device streaming ASR engine for iOS.
Would love to get feedback or benchmark ideas!
If anyone's curious to try it on their device, I’m happy to add you to TestFlight — just DM me.
https://github.com/make1986/ios-streaming-asr-offline