PATENT CLAIM ANALYSIS

Application Number: 15878113
Application Type: Utility
Filing Date: 2018-01
Publication Date: 2019-05
Patent Classification: ["704", "232000"]

Abstract:
The disclosed technology teaches a deep end-to-end speech recognition model, including using multi-objective learning criteria to train a deep end-to-end speech recognition model on training data comprising speech samples temporally labeled with ground truth transcriptions. The multi-objective learning criteria updates model parameters of the model over one thousand to millions of backpropagation iterations by combining, at each iteration, a maximum likelihood objective function that modifies the model parameters to maximize a probability of outputting a correct transcription and a policy gradient function that modifies the model parameters to maximize a positive reward defined based on a non-differentiable performance metric which penalizes incorrect transcriptions in accordance with their conformity to corresponding ground truth transcriptions; and upon convergence after a final backpropagation iteration, persisting the modified model parameters learned by using the multi-objective learning criteria with the model to be applied to further end-to-end speech recognition.

Claim (Index 9):
The method of  claim 1 , wherein the policy gradient function is applied using self-critical sequence training (abbreviated SCST).

Metadata:
- Claim Count in Document: 15.0
- Percentile: 86.0
- Lexical Diversity: 1.77647
- Patent Class: 704.0
- Transitional Phrase Type: none
- Component Type: 0
- Foreign Priority: False
- Related Applications: ['15358102', '15258799', '15397327', '15843047', '15258836']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.290616106118182
- 35 USC 102 Novelty (BERT): 0.5169617440847384
- Combined Prediction Score: 0.3132506699148377
- Mean Citation Score: 244.84407
- Max Citation Score: 276.69717
- Similarity Product: 159.4736809792328

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