Gate News: On March 10, Tether’s BrainWhisperer project achieved an accuracy of 98.3% in converting brain signals to text during the latest testing. In the Brain-to-Text '25 Kaggle competition, it ranked fourth out of 466 teams with a 1.78% Word Error Rate (WER). The system uses an architecture based on OpenAI’s Whisper model, combined with LoRA fine-tuning techniques, and decodes cortical electrical signals into text through a multi-model ensemble pipeline. Additionally, Tether is simultaneously advancing research on cross-individual signal decoding frameworks and non-invasive brain-computer interface (BCI) devices, and has released the Brain OS open-source brain operating system on the QVAC platform.
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