PATENT CLAIM ANALYSIS

Application Number: 16108110
Application Type: Utility
Filing Date: 2018-08
Publication Date: 2020-01
Patent Classification: ["704", "232000"]

Abstract:
Systems and methods are disclosed for end-to-end neural networks for speech recognition and classification and additional machine learning techniques that may be used in conjunction or separately. Some embodiments comprise multiple neural networks, directly connected to each other to form an end-to-end neural network. One embodiment comprises a convolutional network, a first fully-connected network, a recurrent network, a second fully-connected network, and an output network. Some embodiments are related to generating speech transcriptions, and some embodiments relate to classifying speech into a number of classifications.

Claim (Index 6):
The speech recognition system of  claim 1 , wherein the recurrent neural network comprises a plurality of recurrent neural network layers.

Metadata:
- Claim Count in Document: 50.0
- Percentile: 96.0
- Lexical Diversity: 1.63793
- Patent Class: 704.0
- Transitional Phrase Type: none
- Component Type: 0
- Foreign Priority: False
- Related Applications: ['16108107', '16108109', '15243838', '14877673', '14811939']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.3318759696860737
- 35 USC 102 Novelty (BERT): 0.5532433770572736
- Combined Prediction Score: 0.3540127104231937
- Mean Citation Score: 337.846998
- Max Citation Score: 403.5461
- Similarity Product: 294.84939762287144

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