PATENT CLAIM ANALYSIS

Application Number: 16444890
Application Type: Utility
Filing Date: 2019-06
Publication Date: 2020-01
Patent Classification: ["704", "233000"]

Abstract:
There are disclosed devices, system and methods for desired signal spotting in noisy, flawed environments by identifying a signal to be spotted, identifying a target confidence level, and then passing a pool of cabined arrays through a comparator to detect the identified signal, wherein the cabined arrays are derived from respective distinct environments. The arrays may include plural converted samples, each converted sample include a product of a conversion of a respective original sample, the conversion including filtering noise and transforming the original sample from a first form to a second form. Detecting may include measuring a confidence of the presence of the identified signal in each of plural converted samples using correlation of the identified signal to bodies of known matching samples. If the confidence for a given converted sample satisfies the target confidence level, the given sample is flagged.

Claim (Index 12):
The apparatus of  claim 10 , wherein the bodies of known matching samples are artificial intelligence (AI) created reference signals created by the comparator during use of the comparator to spot the desired signal in the given call sample.

Metadata:
- Claim Count in Document: 17.0
- Percentile: 100.0
- Lexical Diversity: 2.09589
- Patent Class: 704.0
- Transitional Phrase Type: none
- Component Type: 0
- Foreign Priority: False
- Related Applications: ['16362105', '16022370', '13482841', '10699909', '10996811']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.2645313262460815
- 35 USC 102 Novelty (BERT): 0.5255568889051856
- Combined Prediction Score: 0.2906338825119919
- Mean Citation Score: 183.387244
- Max Citation Score: 321.4618
- Similarity Product: 248.06970305306908

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

Dataset: test