Voice AI that hears what other models miss.
Joined October 2020
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Introducing A5S Async V1: the world's most accurate speech recognition model for speaker-attributed transcription.
#1 on VoiceArena, ahead of ElevenLabs, AssemblyAI, Deepgram, NVIDIA, Meta & more.
The next-best model makes 41% more errors across 5 public benchmarks.
And yes, every lab says they're #1. So we open-sourced our benchmark.
Try it now👇
AirCaps AI retweeted
Blows my mind what a tiny team of AI-pilled engineers can pull off! 🤯
@tryaircaps’ A5S Async v1 ranks #1 on VoiceArena for figuring out who said what. Across their five public benchmarks, the next-best model makes 41% more errors. They’ve open-sourced the benchmark so you can check the results yourself.
Small team. Big swing. Incredible work, @madlavak!
cc @vkhosla @khoslaventures
Introducing A5S Async V1: the world's most accurate speech recognition model for speaker-attributed transcription.
#1 on VoiceArena, ahead of ElevenLabs, AssemblyAI, Deepgram, NVIDIA, Meta & more.
The next-best model makes 41% more errors across 5 public benchmarks.
And yes, every lab says they're #1. So we open-sourced our benchmark.
Try it now👇
AirCaps AI retweeted
Really excited about this model. The gap between us and previously SOTA STT models like ElevenLabs, Nvidia, AssemblyAI, Google, Meta is surprisingly large. Proud of our tiny team taking on the titans. Try it out on the AirCaps API, first 5h free.
Introducing A5S Async V1: the world's most accurate speech recognition model for speaker-attributed transcription.
#1 on VoiceArena, ahead of ElevenLabs, AssemblyAI, Deepgram, NVIDIA, Meta & more.
The next-best model makes 41% more errors across 5 public benchmarks.
And yes, every lab says they're #1. So we open-sourced our benchmark.
Try it now👇
AirCaps AI retweeted
🏆 A new leader on the Voice Arena Diarization + ASR board: AirCaps A5S Async v1 joins the 14 systems already scored and enters at rank #1.
To put this result in context, we evaluated all 15 systems on the same 139 held-out conversations with 2–8 speakers, counting overlapping speech throughout. cpWER measures how accurately a transcript captures words and assigns them to the right speakers.
AirCaps A5S Async v1 scores 23.89% cpWER overall and leads in both settings, with 24.91% cpWER in-person and 17.47% in online calls.
What's particularly interesting is where this lead comes from. AirCaps and Nemotron 3.5 Transcribe (#2) miss a similar share of words (9.29% vs. 8.32%), but AirCaps has a substantially lower substitution rate (10.88% vs. 18.43%) and fewer insertions (3.72% vs. 5.68%).
AirCaps maintains its lead when we resample the 139 conversations. Its overall cpWER showing a 95% confidence interval of 19.47%–28.58%.
Congratulations to the @tryaircaps team on the launch! 👏🏻
VoiceArena independently tested A5S Async v1 on 139 natural conversations with heavy overlap and up to 8 speakers.
AirCaps ranked #1 of 15 models at 23.88% cpWER, vs. 32.43% for NVIDIA Nemotron 3.5 Transcribe (released a week earlier) and 35.73% for the previous leader, ElevenLabs Scribe v2.
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A5S Async v1 ships with support for 9 languages, key-term prompting, and smart formatting.
Try it in the AirCaps console. Your first 5 hours are free:
aircaps.ai/models/a5s-async
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Introducing AirCaps Diarization-v1: the world's most accurate speaker diarization model.
Beats every leading model across 7 popular diarization benchmarks.
61–71% fewer errors than leading cloud ASR providers with built-in diarization (ElevenLabs, AssemblyAI, Meta and Grok). 2.5x fewer than ElevenLabs Scribe v2, the best of them.
12.03% DER vs. 13.21% for DiariZen Large v2 and 13.44% for pyannoteAI Precision-3.
Built for distant mics, noisy rooms and overlapping speech.
Benchmarks, evaluation code & methodology open-sourced. Examples & access:
research.aircaps.com/diariza…
Introducing A5S V2: SOTA streaming speech-to-text for the real world.
Ranks ahead of eight leading proprietary cloud streaming speech models in a real-world accuracy evaluation derived from four public noisy, multi-talker datasets.
A5S V2 achieves a 26.27% word error rate across the fixed four-corpus evaluation, beating ElevenLabs, Meta, AssemblyAI, OpenAI, xAI, Deepgram, and Google. The closest cloud model, ElevenLabs Scribe v2 Realtime, scored 26.64% WER.
36.7% lower WER than Nemotron. 47.9% lower than Whisper Streaming.
Runs locally on iPhone & MacBook, with 50 ms / 44 ms mean finalization latency in our device trials.
Built for noisy rooms, distant microphones, and overlapping speech.
Demos, benchmarks & evaluation access:
research.aircaps.com/a5sv2
Today, we’re publicly launching the AirCaps Audio Research Lab.
Real-world audio is 10x harder to understand than the digital world, and voice is far from “solved.”
We’re building fully streaming speech and audio models for the physical world: target speaker extraction, far-field enhancement, diarization, separation, and speech-to-text.
Our models are a step function ahead of leading cloud speech models in the hardest acoustic environments, while running on edge on consumer hardware.
See real demos: research.aircaps.com/