IEEE

A Sub-0.8-pJ/bit Universal Soft-Detection Decoder Using ORBGRAND

Abstract: Guessing random additive noise decoding (GRAND) has enabled the practical implementation of maximum likelihood (ML) or near-ML decoding, shifting the paradigm of code-specific decoder design ...
GitHub

flinkerlab/neural_speech_decoding

Our ECoG to Speech decoding framework is initially described in A Neural Speech Decoding Framework Leveraging Deep Learning and Speech Synthesis. We present a novel deep learning-based neural speech ...
the-decoder

AI benchmarks are broken and the industry keeps using them anyway, study finds

AI benchmarks are pretty unreliable, Epoch AI finds: Scores shift a lot based on prompt wording, temperature settings, or which testing tool is used. The API provider causes the widest swings in ...
IEEE

Enhancing the Classification Accuracy of EEG-Informed Inner Speech Decoder Using Multi-Wavelet Feature and Support Vector Machine

Abstract: Speech involves the synchronization of the brain and the oral articulators. Inner speech, also known as imagined speech or covert speech, refers to thinking in the form of sound without ...