mnbbrown
- 1. Soniox (stt-async-v4): +176 new cases, running total 176/248 (71.0%)
- 2. ElevenLabs (scribe_v2): +26 new cases, running total 202/248 (81.5%)
- 3. Speechmatics (enhanced): +12 new cases, running total 214/248 (86.3%)
- 4. NVIDIA Parakeet (TDT 0.6B v2): +6 new cases, running total 220/248 (88.7%)
- 5. Mistral (voxtral-mini): +3 new cases, running total 223/248 (89.9%)
- 6. Gladia: +2 new cases, running total 225/248 (90.7%)
- 7. AssemblyAI (universal-2): +1 new cases, running total 226/248 (91.1%)
- 8. Deepgram (nova-3): +1 new cases, running total 227/248 (91.5%)
- 9. Cohere (transcribe-03-2026): +0 new cases, running total 227/248 (91.5%)
- 10. AssemblyAI (universal-3-pro): +0 new cases, running total 227/248 (91.5%)
Soniox (stt-async-v4): 176/248 (71.0%) ElevenLabs (scribe_v2): 170/248 (68.5%) AssemblyAI (universal-3-pro): 166/248 (66.9%) Deepgram (nova-3): 158/248 (63.7%) AssemblyAI (universal-2): 148/248 (59.7%) Cohere (transcribe-03-2026): 148/248 (59.7%) Speechmatics (enhanced): 134/248 (54.0%)
P.s. how do I get this to render correctly on here?
The dataset is ~100 8kHz call recordings with gnarly UK accents (which I consider to be the final boss of english language ASR). It seems like it's SOTA.
Where it does fall down seems to be the latency distribution but I'm testing against the API. Running it locally will no doubt improve that?
Founder-led sales, from the perspective of a Founder, leading sales
The Economics of Model Intelligence
Using the node 18 native test runner with TypeScript and React
Company: We're the UK's fastest growing AI voice company (~30% MoM) - very deeply focused on the trades industry right now (think your friendly neighbourhood plumbing company).
We're a small but experienced team hiring 3 more to join:
- Founding Engineer - Founding SDR - Founding Operations Lead (customer success)
Tech: GKE, python, postgres, telephony/media streaming, realtime LLMs, contextual eou detection, the occasional REST API.
https://careers.elyos.ai/ or message me - matt (at) elyos.ai
Mention bananas for extra kudos.
20 days, one porsche, and a Greek wedding
Defining AI Tools in Python
Async Pytest in Python 3.11+
Ask HN: iOS STT for postcodes, addresses better than deepgram?
Why is iOS speech to text so much better at numbers, addresses and postcodes than Deepgram, whisper, etc?It nails them - the rest are mediocre at best. Does anybody know of a model that's accurate with this sort of data?
Very familiar with BMSs but the lack of open standards and protocols has been extremely frustrating - makes me appreciate how good we have it with HTTP, etc.
Lots say they support BACnet but that’s only if they’ve been configured and the points exported, etc.
Haystack is a great step forward for labelling too but adoption seems fill with complexity :)
It's a very fun mix of hardware (for data collection), and crazy SQL queries to model energy flows between buildings, solar, batteries, etc. Considering just one building is pretty easy:
consumption = imported - exported + generated - stored + dispatched. carbon = carbon intensity * imported cost = tariff * imported
but then you add a site with a couple of buildings, solar on one of them, grid limited exports, etc modelling these flows is challenging. Like consider the case where one building got 10% of it's imported power from another building's excess solar, then calculating carbon becomes more difficult.
and once you've figured all that - then you have to figure out what makes commercial sense to do next.. install a battery, expand solar, move onto a TOU tariff, do nothing - and that's a whole other world of optimisation problems.
Ask HN: Please stop hosting engineering blogs on medium
So much knowledge stuck behind a paywall.
RouterPi – A Compute Module 4 Router
Debian for Embedded Systems – Seriously?
Prometheus exporter for Drayton Wiser smart thermostats
Playing Blue (Da Ba Dee) with Stepper Motors [video]
URLs with spaces are invalid.. or are they?
GoCardless is used for domestic and international payments by 75,000+ organisations and counting, processing more than $30 billion across 30 countries.
Come work on new products, or gnarly scaling challenges.
Stack: Ruby, Rails, PostgreSQL, GCP, React
https://boards.greenhouse.io/gocardless or DM me.
OpenAI’s Code Interpreter Is About to Remake Finance
A privacy-preserving token usage pattern for microservices
It does signature checking and some and some other helpful things.