SPEECH PROCESSING AND BRAIN
S I G N A T U R E S O F S P E E C H , PA R T I C U L A R LY I N
D I S T I N G U I S H I N G T R U E / FA L S E O R Y E S / N O
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”, 2011 . 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”