PATENT CLAIM ANALYSIS

Application Number: 15905728
Application Type: Utility
Filing Date: 2018-02
Publication Date: 2018-07
Patent Classification: ["704", "260000"]

Abstract:
A system and method are presented for outlier identification to remove poor alignments in speech synthesis. The quality of the output of a text-to-speech system directly depends on the accuracy of alignments of a speech utterance. The identification of mis-alignments and mis-pronunciations from automated alignments may be made based on fundamental frequency methods and group delay based outlier methods. The identification of these outliers allows for their removal, which improves the synthesis quality of the text-to-speech system.

Claim (Index 15):
A method for synthesizing speech in a text-to-speech system, wherein the system comprises at least a speech database, a database capable of storing Hidden Markov Models, and a synthesis filter, the method comprising the steps of:\n a. identifying outlying results in audio files from the speech database and removing the outlying results before model training; b. converting a speech signal from the speech database into parameters and extracting the parameters from the speech signal; c. training Hidden Markov Models using the extracted parameters from the speech signal and using the labels from the speech database to produce context dependent Hidden Markov Models; d. storing the context dependent Hidden Markov Models in the database capable of storing Hidden Markov Models; e. inputting text and analyzing the text, wherein said analyzing comprises extracting labels from the text; f. utilizing said labels to generate parameters from the context dependent Hidden Markov Models; g. generating an other signal from the parameters; h. inputting the other signal and the parameters into the synthesis filter; and i. producing synthesized speech as the other signal passes through the synthesis filter.

Metadata:
- Claim Count in Document: 47.0
- Percentile: 88.0
- Lexical Diversity: 1.64
- Patent Class: 704.0
- Transitional Phrase Type: open
- Component Type: 1
- Foreign Priority: False
- Related Applications: ['14737080', '13959171', '15850106', '14069492', '14069510']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.2890386898153256
- 35 USC 102 Novelty (BERT): 0.6069525018635609
- Combined Prediction Score: 0.3208300710201491
- Mean Citation Score: 342.299508
- Max Citation Score: 599.50775
- Similarity Product: 475.9413491423726

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

Dataset: test