SPEECH PROCESSING AND BRAIN SIGNATURES OF SPEECH, PARTICULARLY IN DISTINGUISHING TRUE/FALSE OR YES/NO RESPONSES  Speech processing can refer either to a device that receives and interprets speech then performing a command in response or a machine that interprets brain wave signals related to thoughts of speech then performing a command.  The brain quickly interprets speech; this includes understanding a statement based on semantics, grammar, and intonation (Buzo ). Goal is to create a machine that can do the same and allow LIS patients to communicate effectively.  There’s little difference between the psychophysiological responses and brain signatures of an objectively true statement and those of a delusional (subjectively true) statement. (Langleben )  The brain shows increased activity to noises that have pitches or are decibels outside that of everyday speech. (Zatorre )  Through the processing of brain signatures through BMI (or BCI) to a speech synthesizer, individuals in a locked-in state can form speech and potentially engage in verbal conversation. (Guenther )

To create these communication devices, the first step is to create binary communication devices though the processing of Yes/No thinking. This is done by first semantic classical conditioning cortically evoked responses to the meaning of a word or sentence

CITATIONS  Besserve & Co., “Extraction of functional information from ongoing brain electrical activity”, Tubingen, Germany.  Buzo & Co., “Word Error Rate Improvement and Complexity Reduction in Automatic Speech Recognition”, 2011 Speech Technology and Human Computer Dialogue.  Guenther & Co., "Brain-machine interfaces for real-time speech synthesis”, 2011 Annual International Conference of IEEE.  Henig, R., “Looking for the Lie”, New York Times.  Langleben & Co., “True lies: delusions and lie-detection technology”, Neuroethics Publications Center for Neuroscience & Society.  Mozsary & Co., “Comparison of feature extraction methods for speech recognition in noise-free and in traffic noise environment”, Speech Technology and Human-Computer Dialogue.

 Ruf & Co., “Semantic Classical Conditioning and Brain-Computer Interface Control: Encoding of Affirmative and Negative Thinking”.  Schipor & Co., “Towards a multimodal emotion recognition framework to be integrated in a Computer Based Speech Therapy System”, 2011, Speech Technology and Human-Computer Dialogue.  Sundaram & Co., “Experiments in context-independent recognition of non-lexical ‘yes’ or ‘no’ responses”, 2011, Acoustics, Speech and Signal Processing.  Zatorre & Co., “Lateralization of phonetic and pitch discrimination in speech processing”