PATENT CLAIM ANALYSIS

Application Number: 15894245
Application Type: Utility
Filing Date: 2018-02
Publication Date: 2018-06
Patent Classification: ["704", "233000"]

Abstract:
Disclosed herein are systems, methods, and computer-readable storage media for detecting voice activity in a media signal in an augmented, multi-tier classifier architecture. A system configured to practice the method can receive, from a first classifier, a first voice activity indicator detected in a first modality for a human subject. Then, the system can receive, from a second classifier, a second voice activity indicator detected in a second modality for the human subject, wherein the first voice activity indicator and the second voice activity indicators are based on the human subject at a same time, and wherein the first modality and the second modality are different. The system can concatenate, via a third classifier, the first voice activity indicator and the second voice activity indicator with original features of the human subject, to yield a classifier output, and determine voice activity based on the classifier output.

Claim (Index 5):
The method of  claim 1 , wherein the combining of the first classifier output from the first classifier with the second classifier output from the second classifier further comprises:\n performing late fusion of original features associated with the human subject using weighted majority voting.

Metadata:
- Claim Count in Document: 50.0
- Percentile: 88.0
- Lexical Diversity: 2.73333
- Patent Class: 704.0
- Transitional Phrase Type: none
- Component Type: 0
- Foreign Priority: False
- Related Applications: ['13974453', '10137633', '12433143', '12515048', '15659016']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.2634716531483682
- 35 USC 102 Novelty (BERT): 0.517388931493161
- Combined Prediction Score: 0.2888633809828475
- Mean Citation Score: 174.20136599999995
- Max Citation Score: 326.99536
- Similarity Product: 280.7241144955444

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

Dataset: test