Real-time decoding of question-and-answer speech dialogue using human cortical activity
Excerpt: ABSTRACT: Natural communication often occurs in dialogue, differentially engaging auditory and sensorimotor brain regions during listening and speaking. However, previous attempts to decode speech directly from the human brain typically consider listening or speaking tasks in isolation. Here, human participants listened to questions and responded aloud with answers while we used high-density electrocorticography (ECoG) recordings to detect when they heard or said an utterance and to then decode the utterance’s identity. Because certain answers were only plausible responses to certain questions, we could dynamically update the prior probabilities of each answer using the decoded question likelihoods as context. We decode produced and perceived utterances with accuracy rates as high as 61% and 76%, respectively (chance is 7% and 20%). Contextual integration of decoded question likelihoods significantly improves answer decoding. These results demonstrate real-time decoding of speech in an interactive, conversational setting, which has important implications for patients who are unable to communicate. [Science fiction writers have been predicting some form of “speech-writer” since at least the 1940s. Starting with the Dictaphone-type systems of the 1950s up through the speech-recognition systems of today, this is the first serious experiment I know of to do that job directly from THOUGHTS rather than spoken words. If they can bring it to market, millions who are speech-impaired will suddenly be given a voice. I wonder if it can eventually be applied to the more vocal animals (dolphins, whales, chimps, et cetera)? Though borderline technical, this article ought to be easily understandable at least as far as the sub-heading “Methods.” Ron P.]
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