Haptic communication system using cutaneous actuators for simulation of continuous human touch
摘要
說明書
The feature extraction component 236 receives the signals 216, 256 and extracts features 408a, 408b, etc., from the signals 216, 256. The features 408a, 808b, etc., facilitate training of the machine learning circuit 242. In one embodiment, redundant input data in the signals 216, 256 such as the repetitiveness of signals or speech patterns may be transformed into the reduced set of features 408. The extracted features 408 contain the relevant information from the signals 216, 256 such that the machine learning circuit 242 is trained by using this reduced representation instead of the complete initial data. The features 408 corresponding to the signals 216, 256 are used for training the machine learning circuit 242 based on known touch signatures stored in the touch signatures store 412 and known speech subcomponents stored in the speech subcomponents store 416 that correspond to those features.
