PATENT CLAIM ANALYSIS

Application Number: 16051672
Application Type: Utility
Filing Date: 2018-08
Publication Date: 2019-02
Patent Classification: ["704", "200000"]

Abstract:
The present disclosure provides a far field speech acoustic model training method and system. The method comprises: blending near field speech training data with far field speech training data to generate blended speech training data, wherein the far field speech training data is obtained by performing data augmentation processing for the near field speech training data; using the blended speech training data to train a deep neural network to generate a far field recognition acoustic model. The present disclosure can avoid the problem of spending a lot of time costs and economic costs in recording the far field speech data in the prior art; and reduce time and economic costs of obtaining the far field speech data, and improve the far field speech recognition effect.

Claim (Index 6):
The method according to  claim 1 , wherein the using the blended speech training data to train a deep neural network to generate a far field recognition acoustic model comprises:\n obtaining speech feature vectors by performing pre-processing and feature extraction for the blended speech training data; training by taking the speech feature vectors as input of the deep neural network and speech identities in the speech training data as output of the deep neural network, to obtain the far field recognition acoustic model.

Metadata:
- Claim Count in Document: 6.0
- Percentile: 96.0
- Lexical Diversity: 2.2931
- Patent Class: 704.0
- Transitional Phrase Type: none
- Component Type: 0
- Foreign Priority: True
- Related Applications: ['15934566', '15042309', '15231909', '15980208', '15344110']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.2755679609562728
- 35 USC 102 Novelty (BERT): 0.4933018086831203
- Combined Prediction Score: 0.2973413457289576
- Mean Citation Score: 247.22745
- Max Citation Score: 252.8502
- Similarity Product: 217.4188030094862

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

Dataset: test