PATENT CLAIM ANALYSIS

Application Number: 16022026
Application Type: Utility
Filing Date: 2018-06
Publication Date: 2019-11
Patent Classification: ["704", "232000"]

Abstract:
A speaker recognition system includes a previously-trained joint neural network. An enrollment machine of the speaker recognition system is configured to operate the previously-trained joint neural network to enroll a new speaker based on audiovisual data featuring the newly enrolled speaker. A recognition machine of the speaker recognition system is configured to operate the previously-trained joint neural network to recognize a previously-enrolled speaker based on audiovisual data featuring the previously-enrolled speaker.

Claim (Index 19):
A method for speaker recognition, the method comprising:\n training a joint neural network to identify a speaker of a plurality of speakers based on a plurality of labelled input vectors, wherein:\n a labelled input vector includes an input vector comprising audio data and video data featuring a speaker of the plurality of speakers, and a speaker identifier indicating the speaker; and \n the joint neural network is configured to output, for an input vector and for each candidate speaker of the plurality of speakers, a confidence indicating a likelihood that a speaker featured in one or more of the audio data and the video data of the input vector is the candidate speaker; \n enrolling a newly enrolled speaker based on an enrollment input vector comprising audio data and video data, by operating the previously-trained joint neural network to receive the enrollment input vector, and extract an enrollment vector output by a hidden layer of the previously-trained joint neural network; and recognizing the newly enrolled speaker based on a test input vector comprising audio data and video data, by:\n operating the previously-trained joint neural network to receive the test input vector, and extract a test feature vector output by the hidden layer of the previously-trained joint neural network; and \n comparing the test feature vector to the enrollment vector.

Metadata:
- Claim Count in Document: 50.0
- Percentile: 94.0
- Lexical Diversity: 2.3871
- Patent Class: 704.0
- Transitional Phrase Type: open
- Component Type: 1
- Foreign Priority: False
- Related Applications: ['15966667', '15013580', '16006405', '14281373', '14612830']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.2621098671666232
- 35 USC 102 Novelty (BERT): 0.4678813978158554
- Combined Prediction Score: 0.2826870202315464
- Mean Citation Score: 187.065492
- Max Citation Score: 209.0483
- Similarity Product: 179.61148350306752

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

Dataset: test