PATENT CLAIM ANALYSIS

Application Number: 15926408
Application Type: Utility
Filing Date: 2018-03
Publication Date: 2019-09
Patent Classification: ["704", "232000"]

Abstract:
Methods, systems and apparatuses are provided to perform a continuous-to-continuous mapping of neural signal data received from one or more body sensors connected to an user wherein the one or more body sensors monitors at least neural activities of the user of a sub-vocalized voice at a sensory level and sends the neural signal data to a processor. The processor receives the neural signal data in an iterative closed loop to train the processor and to generate a sufficiently large data set in the neural signal domain to link to a produced voice domain. The processor constructs a common feature space which associates the neural signal domain with the produced voice domain wherein the common feature space implicitly extracts features related to audio communications for linking neural signal domain data to the produced voice data without requiring any prior feature classification of the received neural signal data.

Claim (Index 14):
A sub-vocalization system of imagined speech, comprising:\n a plurality of body sensors; a processor, that executes instructions contained in a non-transitory computer read-able medium, to perform a continuous-to-continuous mapping of neural signal data received from one or more body sensors from the plurality of body sensors connected to an user wherein the one or more body sensors monitors at least neural activities of the user of a sub-vocalized voice at a sensory level and sends the neural signal data to the processor; and an artificial neural network (ANN) to model the continuous-to-continuous mapping of neural signal data received from the one or more body sensors connected to the user, the processor configured to:\n process, a set of neural signal data received from the one or more body sensors, in an iterative closed loop for training the processor wherein the training generates a sufficiently large data set in the neural signal domain from the neural signal data to link to a produced voice domain; \n construct, a common feature space, which associates the neural signal domain with the produced voice domain to produce audio communications wherein the common feature space implicitly extracts features related to audio communications, using the sufficiently large data set, by the common feature space to link neural signal domain data to the produced voice data without requiring any prior feature classification of the received neural signal data; \n learn, using a data learning, by performing iterations of the closed loop training of the processor of a mapping of the common feature space for a set of common neural signal domain activity, and by applying a set of ANN based algorithms of the ANN while performing a data modeling of the common feature space: and \n perform a first function to map the neural signal domain, and a second function to target the map of the first function to the produced voice domain to reproduce the subvocalized voice wherein a f(x) is used by the first function to map to the common feature space, and an inverse G-1(x) is used by the second function for targeting to the produced voice domain.

Metadata:
- Claim Count in Document: 6.0
- Percentile: 90.0
- Lexical Diversity: 2.06849
- Patent Class: 704.0
- Transitional Phrase Type: open
- Component Type: 1
- Foreign Priority: False
- Related Applications: ['15350293', '15697923', '13738868', '11169265', '14835192']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.2366712873915037
- 35 USC 102 Novelty (BERT): 0.4633446445420728
- Combined Prediction Score: 0.2593386231065606
- Mean Citation Score: 161.128242
- Max Citation Score: 166.00447
- Similarity Product: 130.43109128064273

Labels:
- Claim Label 101: 1
- Claim Label 102: 1
- Claim Label 103: 1
- Claim Label 112: 1
- Combined Label: 1
- Label 101 Adjusted: 1

Dataset: test