PATENT CLAIM ANALYSIS

Application Number: 15758280
Application Type: Utility
Filing Date: 2018-03
Publication Date: 2018-09
Patent Classification: ["704", "266000"]

Abstract:
A training method for multiple personalized acoustic models, and a voice synthesis method and device, for voice synthesis. The method comprises: training a reference acoustic model, based on first acoustic feature data of training voice data and first text annotation data corresponding to the training voice data (S 11 ); acquiring voice data of a target user (S 12 ); training a first target user acoustic model according to the reference acoustic model and the voice data (S 13 ); generating second acoustic feature data of the first text annotation data, according to the first target user acoustic model and the first text annotation data (S 14 ); and training a second target user acoustic model, based on the first text annotation data and the second acoustic feature data (S 15 ).

Claim (Index 15):
The method according to  claim 2 , wherein training the first target user acoustic model according to the reference acoustic model, the third acoustic feature data, and the second text annotation data comprises:\n obtaining a neural network structure of the reference acoustic model; updating parameters in the neural network structure of the reference acoustic model by performing an iterative operation via a neural network adaptive technology according to the third acoustic feature data, the second text annotation data and the neural network structure of the reference acoustic model, to obtain the first target user acoustic model.

Metadata:
- Claim Count in Document: 1.0
- Percentile: 90.0
- Lexical Diversity: 3.23913
- Patent Class: 704.0
- Transitional Phrase Type: none
- Component Type: 0
- Foreign Priority: True
- Related Applications: ['15758214', '11549412', '10329181', '10355296', '12639164']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.3483550694857011
- 35 USC 102 Novelty (BERT): 0.5383978183712795
- Combined Prediction Score: 0.367359344374259
- Mean Citation Score: 349.3658660000001
- Max Citation Score: 391.96466
- Similarity Product: 299.94421483624933

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