PATENT CLAIM ANALYSIS

Application Number: 16006405
Application Type: Utility
Filing Date: 2018-06
Publication Date: 2019-11
Patent Classification: ["704", "232000"]

Abstract:
Computing devices and methods utilizing a joint speaker location/speaker identification neural network are provided. In one example a computing device receives a multi-channel audio signal of an utterance spoken by a user. Magnitude and phase information features are extracted from the signal and inputted into a joint speaker location/speaker identification neural network that is trained via utterances from a plurality of persons. A user embedding comprising speaker identification characteristics and location characteristics is received from the neural network and compared to a plurality of enrollment embeddings extracted from the plurality of utterances that are each associated with an identity of a corresponding person. Based at least on the comparisons, the user is matched to an identity of one of the persons, and the identity of the person is outputted.

Claim (Index 13):
The method of  claim 12 , further comprising:\n utilizing the location characteristics of the user embedding to determine an angular orientation of the user with respect to a microphone array that captured the multi-channel audio signal of the utterance spoken by the user; and outputting the angular orientation along with the identity of the person matched to the user.

Metadata:
- Claim Count in Document: 37.0
- Percentile: 94.0
- Lexical Diversity: 1.94286
- Patent Class: 704.0
- Transitional Phrase Type: open
- Component Type: 1
- Foreign Priority: False
- Related Applications: ['15966667', '15995480', '15666806', '14846187', '14228469']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.2521732478937966
- 35 USC 102 Novelty (BERT): 0.492699296200174
- Combined Prediction Score: 0.2762258527244343
- Mean Citation Score: 216.16387000000003
- Max Citation Score: 228.4664
- Similarity Product: 160.36512929577827

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