AssemblyAI

Announcing Universal-2, our next-generation speech-to-text model! Building on Universal-1's industry-leading performance, we've made significant improvements in just 6 months, focusing on areas that matter most for real-world conversations: - 24% better at handling proper nouns - 21% improvement in alphanumeric accuracy - 15% enhanced text formatting - Maintains 30% reduction in hallucinations versus other speech-to-text models like Whisper - 73% of users prefer Universal-2 outputs compared to Universal-1 What makes Universal-2 special isn't just better accuracy - it's solving the hardest challenges in conversational AI. From handling messy real-world speech to accurately capturing proper nouns, phone numbers, and formatting, Universal-2 delivers transcripts that are both accurate and clean. Universal-2 is available today through our API. Start building on Universal-2 today: https://lnkd.in/ex2QU_SP

We've added another integration! You can now use AssemblyAI's Streaming Speech-to-Text model in LiveKit to build smart real-time applications! Shout out to our Senior Developer Educator Ryan O'Connor who worked with the LiveKit team to build this integration for their AI Agents framework to allow developers to perform speech-to-text with AssemblyAI in real-time within the context of LiveKit applications. Follow along with our detailed, easy-to-follow tutorial about how to use the integration here: https://lnkd.in/e2UdvsNX

Happy New Year! As we move into 2025, we’re first taking a moment to look back and reflect on some of our top AssemblyAI moments of 2024: 📹 Our YouTube channel hit 150K followers. Follow along with our videos on AI innovations, coding tutorials, and more: https://lnkd.in/gGthPrbc ✍️ We published more than 150 tutorials, deep dives, and customer stories on our blog to help you build with speech AI - https://lnkd.in/ej7yNxzW 💡 We launched Assembly Required - a series of candid conversations with AI founders sharing insights, learnings, and the highs and lows of building a company. You can watch all 5 episodes of the series here: https://lnkd.in/efMYzmht 👨💻 We released 4 SDKs and 6 integrations to help developers more easily integrate Speech AI into their apps. Learn more here: https://lnkd.in/eRH9MfiB Our product, research, and engineering teams were busy this year! We launched new models and important updates to our API, including Universal We released our Universal series of Speech-to-Text models, releasing Universal-1 in April and following up with the recent release of Universal-2. The Universal series was built specifically to power real-life use cases and to provide developers with best-in-class Speech-to-Text on which they can build new products and features for modern, AI-powered user experiences. Best and Nano tiers Concurrent with our release of Universal-1, we introduced our Best and Nano tiers, providing developers with greater flexibility and pricing options for how they build with our Speech-to-Text models. Cost and latency reductions We reduced our Speech-to-Text pricing by 43% for async and 37% for streaming; and we decoupled and reduced pricing for our Audio Intelligence models. You can see our up-to-date pricing here. Additionally, we introduced major improvements to our API’s inference latency, with the majority of audio files now completing in well under 45 seconds regardless of audio duration. Free offering improvements We improved our free offering, offering $50 in free credits (up to 417 hours of audio transcribed) which automatically roll over after upgrading to our pay-as-you-go pricing. Additionally, free offering users get access to the usage dashboard, billing rates/alerts, and more. Speaker Diarization improvements We added 5 new languages to our Speaker Diarization model, and made it up to 13% more accurate. Automatic Language Detection improvements We improved our Automatic Language Detection, adding 10 new languages for a total of 17, and achieving best-in-class accuracy in 15 of those 17 languages. And so much more! 🎉 Here’s to an even bigger 2025! 🎉

When working with audio recordings that feature multiple speakers, separating and identifying each participant is a crucial step in producing accurate and organized transcriptions. In this detailed tutorial, Patrick Löber teaches you how Multichannel transcription and Speaker Diarization work, what their outputs look like, when to use each feature, and how you can implement them.

Learn how our best-in-class Speech-to-Text model Universal-2 is solving problems in Conversational Intelligence by optimizing Speech-to-Text for real-world use cases.

“It's very important not to just think about the technology first because you want to solve the problem and then figure out what technology can enable it. A lot of times going back to what you can show in a demo with these AI products is really incredible, but what you're not able to do is translate that into a real product at scale.” Listen as Fireflies.ai co-founder and CEO Krish Ramineni discusses how the problem has to come first—and technology second—when thinking about solving problems for users in our latest episode of Assembly Required.

Are Large Language Models (LLMs) just advanced versions of autocomplete? In this YouTube video, we dive deep into how LLMs like ChatGPT, Claude, and Gemini actually choose the next word when generating text. https://lnkd.in/erbfr4dG

Last week, we hosted an awesome Hackathon in NYC! Developers and AI enthusiasts of all levels gathered for a day of building with AssemblyAI and connecting with each other. 🏆 We’re excited to highlight the winning project: Dealty by Slavik Kaushan and Mario Uribe. Slavik and Mario are developers, entrepreneurs, and AI enthusiasts who used AssemblyAI’s streaming speech-to-text and entity detection models to build a Speech AI tool for real estate investment deals. 🥈 The runner-up project was Muse by Arjun S, Ritvij Saxena, and Siddharth P. -  a mental health journaling assistant that the AssemblyAI team agreed we’d buy in the app store immediately. 👏 Finally, we gave a special shoutout to project Say What by Stuart Allen, Nikki Hu, Kirk Enbysk, and Peter Shrieve-Don. They built an AssemblyAI-powered guessing game that turns audio clips into transcriptions for interactive learning. Shoutout to our judging panel: Christy Roach, Peter McKee, and Smitha Kolan! And major thanks to the rest of the AssemblyAI team in attendance, helping run the show: Whitney DeGraaf, Amanda DiNoto, Alberto Santos, Dylan D., Patrick Löber, and Amber J Maillard. Interested in connecting with developers? - Join our Discord: https://lnkd.in/eCFHfYss - Sign up for our newsletter: https://lnkd.in/eReCb87e Thank you to everyone who came out for this event. We can’t wait for the next one!

Voice content moderation with AI: everything you need to know, including: - What is voice content moderation? - The struggles of traditional voice content moderation - AI-powered voice content moderation - How to use AssemblyAI for voice content moderation

💡 New tutorial on our blog! If you're using Zoom, you may know that it allows you to record each participant's audio track separately. In this tutorial, we teach you how to combine this with AssemblyAI's multichannel transcription to generate accurate meeting transcripts.