PATENT CLAIM ANALYSIS

Application Number: 16252353
Application Type: Utility
Filing Date: 2019-01
Publication Date: 2019-07
Patent Classification: ["381", "086000"]

Abstract:
A training system ( 10 ) for a vehicle control unit for detecting hazard sounds, in particular accident sounds, that has at least one interface ( 12 ) for inputting training data ( 15 ) containing an audio signal ( 16 ) and a target reaction signal ( 18 ) in each case, an evaluation unit ( 20 ) that forms an artificial neural network ( 22 ) and is configured for forward propagation of the artificial neural network ( 22 ) with training data ( 14 ) in order to calculate an actual reaction signal ( 24 ), and calculating weightings through backward propagation of the target reaction signal ( 18 ) in the artificial neural network ( 22 ), wherein the weightings are configured to be stored in the vehicle control unit for detecting accident sounds.

Claim (Index 1):
A training system for a vehicle control unit for detecting hazard sounds, in particular accident sounds, that has\n at least one interface, for inputting training data containing an audio signal and a target reaction signal in each case, an evaluation unit forming an artificial neural network, configured for forward propagation of the artificial neural network with training data in order to calculate actual reaction signals, and\n calculating a modified topology of the artificial neural network, in particular weightings, through backward propagation of the target reaction signals in the artificial neural network, \n wherein the topology is configured to be stored in the vehicle control unit for detecting hazard sounds.

Metadata:
- Claim Count in Document: 1.0
- Percentile: 99.0
- Lexical Diversity: 2.11765
- Patent Class: 381.0
- Transitional Phrase Type: none
- Component Type: 0
- Foreign Priority: True
- Related Applications: ['11549699', '11953671', '13997123', '10151438', '14887564']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.6893799379130493
- 35 USC 102 Novelty (BERT): 0.4833919233565367
- Combined Prediction Score: 0.668781136457398
- Mean Citation Score: 149.6074
- Max Citation Score: 155.27223
- Similarity Product: 103.91875520806788

Labels:
- Claim Label 101: 1
- Claim Label 102: 1
- Claim Label 103: 0
- Claim Label 112: 1
- Combined Label: 1
- Label 101 Adjusted: 0

Dataset: test