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This paper investigates the effects of phonetic versus character targets and selective state-space models (Mamba) for intracortical brain-to-text decoding, finding that a GRU-based recurrent decoder remains the strongest performer on the Brain-to-Text '25 benchmark.
This paper evaluates demographic and accent biases in phoneme-based ASR systems, specifically WhisperIPA and ZIPA, using phoneme error rate and a new Soft PER metric, revealing persistent disparities across languages and groups.