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 5):
A method for speech synthesis using a first target user acoustic model, wherein the first target user acoustic model is obtained by training a reference acoustic model based on first acoustic feature data of training speech data and first text annotation data corresponding to the training speech data; obtaining speech data of a target user; training the first target user acoustic model according to the reference acoustic model and the speech data,\n the method for speech synthesis comprises: obtaining a text to be synthesized, and performing word segmentation on the text to be synthesized; performing part-of-speech tagging on the text to be synthesized after the word segmentation, and performing a prosody prediction on the text to be synthesized after the part-of-speech tagging via a prosody prediction model, to generate prosodic features of the text to be synthesized; performing phonetic notation on the text to be synthesized according to a result of the word segmentation, a result of the part-of-speech tagging, and the prosodic features, to generate a result of phonetic notation of the text to be synthesized; inputting the result of phonetic notation, the prosodic features, and context features of the text to be synthesized to the first target user acoustic model, and performing an acoustic prediction on the text to be synthesized via the first target user acoustic model, to generate an acoustic parameter sequence of the text to be synthesized; and generating a speech synthesis result of the text to be synthesized according to the acoustic parameter sequence.

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): 0.3471678423674331
- 35 USC 102 Novelty (BERT): 0.539759329379339
- Combined Prediction Score: 0.3664269910686237
- Mean Citation Score: 349.3658660000001
- Max Citation Score: 391.96466
- Similarity Product: 334.40925613547205

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