SYNTHETICALLY GENERATING INNER SPEECH TRAINING DATA

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United States of America

APP PUB NO 20250118290A1
SERIAL NO

18484282

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Abstract

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Methods and systems are disclosed for synthetically generating inner speech training data. The methods and systems access a collection of overt speech signals representing phonemes, phoneme sounds, words or phrases spoken at least partially using overt speech. The methods and systems transform the collection of overt speech signals into inner speech training data comprising electromyograph (EMG) data representing inner speech corresponding to the phonemes, phoneme sounds, words or phrases spoken at least partially using the overt speech. The methods and systems train a machine learning model to decode inner speech signals into a set of corresponding phonemes, phoneme sounds, words or phrases based on the inner speech training data.

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Patent OwnerAddress
SNAP INC3000 31ST STREET SANTA MONICA CA 90405

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Inventor(s)

Inventor Name Address # of filed Patents Total Citations
Laufer, Yaron Brookline, US 17 40
Meshulam, Meir Princeton, US 2 0
Ziv, Assif Beit Yitzhak-Sha'ar Hefer, IL 8 28

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