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Stimulus reconstruction-based auditory attention decoding from EEG signals is easily fooled: unbalanced datasets inflate decoding accuracy, but a new cross-validation method fixes this.
A new synthetic whispered speech corpus, WhispSynth, closes the data gap in text-to-whisper research by achieving naturalness scores on par with real recordings.
