PATENT CLAIM ANALYSIS

Application Number: 15910720
Application Type: Utility
Filing Date: 2018-03
Publication Date: 2018-09
Patent Classification: ["704", "232000"]

Abstract:
Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for obtaining, by a first sequence-training speech model, a first batch of training frames that represent speech features of first training utterances; obtaining, by the first sequence-training speech model, one or more first neural network parameters; determining, by the first sequence-training speech model, one or more optimized first neural network parameters based on (i) the first batch of training frames and (ii) the one or more first neural network parameters; obtaining, by a second sequence-training speech model, a second batch of training frames that represent speech features of second training utterances; obtaining one or more second neural network parameters; and determining, by the second sequence-training speech model, one or more optimized second neural network parameters based on (i) the second batch of training frames and (ii) the one or more second neural network parameters.

Claim (Index 11):
The method of  claim 9 , wherein determining the reference score associated with the utterance comprises:\n obtaining, by the first decoder, the parameter values for the neural network; obtaining, by the first decoder, data indicating a true transcription of the utterance; and determining, by the first decoder, a reference lattice based on (i) the utterance, (ii) the obtained parameter values, and (iii) the data indicating a true transcription of the utterance.

Metadata:
- Claim Count in Document: 27.0
- Percentile: 90.0
- Lexical Diversity: 3.88889
- Patent Class: 704.0
- Transitional Phrase Type: none
- Component Type: 0
- Foreign Priority: False
- Related Applications: ['14258139', '15013239', '15243838', '14983315', '15843047']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.2681164148096239
- 35 USC 102 Novelty (BERT): 0.5756391177336773
- Combined Prediction Score: 0.2988686851020293
- Mean Citation Score: 303.553824
- Max Citation Score: 476.25327
- Similarity Product: 377.4829858545632

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