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Tether AI Research has unveiled its on-device speech recognition model TranscribePsy, designed for smart glasses and humanoid robots.

43 minutes ago

Tether AI Research has released an open-source multilingual automatic speech recognition (ASR) model named QVAC TranscribePsy, which has around 254 million parameters and can run fully on-device—no audio upload to the cloud required. The company noted the model can process audio from smart glasses connected via Bluetooth or Wi-Fi in near real time, and also operate on onboard processors of humanoid robots. On the Core ML version for iPhone 17 Pro Max, transcribing 10 minutes of audio takes roughly 1.65 seconds. According to its published benchmark data, TranscribePsy achieves a word error rate (WER) of 8.02% on the Open ASR Leaderboard, 6.58% on Multilingual LibriSpeech, and 21.56% on Common Voice. Among six tested smartphones, it is the fastest in speed, approximately 2.6 times faster than the second-fastest model. The model supports 25 European languages for laptops and 8 European languages for mobile phones, with model weights and builds in formats including GGUF and Core ML released under the Apache 2.0 license. Tether CEO Paolo Ardoino stated that he hopes advanced speech AI can run locally on users’ own devices, ensuring data does not leave the device.

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MegaETH ecosystem-based AI trading platform MNX has launched, covering Pre-IPO, computing power, employment, and general election sectors.

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US September unadjusted CPI year-on-year rate hits 3.7%, against expectations of 3.6% and a prior reading of 3.40%

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