PATENT CLAIM ANALYSIS

Application Number: 16215755
Application Type: Utility
Filing Date: 2018-12
Publication Date: 2019-04
Patent Classification: ["381", "094200"]

Abstract:
A system that performs noise estimation for an audio adjustment application comprises a coherence calculator that determines at least one coherence value between microphone signals generated by at least two microphones that each independently senses acoustic energy in a listening space. A first microphone of the at least two microphones generates a first microphone signal from the acoustic energy and a second microphone of the at least two microphones generates a second microphone signal from the acoustic energy. The acoustic energy comprises a combination of an audio signal transduced by one or more speakers and environmental noise of the acoustic energy that is local to the listening space. A noise estimate computation processor determines an estimate of a level of the environmental noise based on the at least one coherence value.

Claim (Index 18):
The computer program product of  claim 17 , further comprising:\n computer readable program code configured to compute a factor from an aggregate of the coherence values for the frequency bands of the first and second plurality of frequency bands to determine the estimate of the level of noise in the listening space.

Metadata:
- Claim Count in Document: 50.0
- Percentile: 98.0
- Lexical Diversity: 2.25
- Patent Class: 381.0
- Transitional Phrase Type: open
- Component Type: 1
- Foreign Priority: False
- Related Applications: ['15875126', '15282652', '14035662', '12636432', '13753162']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.6752724694288486
- 35 USC 102 Novelty (BERT): 0.5490339769027065
- Combined Prediction Score: 0.6626486201762344
- Mean Citation Score: 286.2095040000001
- Max Citation Score: 411.69943
- Similarity Product: 352.41594159199065

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