PATENT CLAIM ANALYSIS

Application Number: 16022823
Application Type: Utility
Filing Date: 2018-06
Publication Date: 2018-11
Patent Classification: ["704", "259000"]

Abstract:
A technique improves training and speech quality of a text-to-speech (TTS) system having an artificial intelligence, such as a neural network. The TTS system is organized as a front-end subsystem and a back-end subsystem. The front-end subsystem is configured to provide analysis and conversion of text into input vectors, each having at least a base frequency, f 0 , a phenome duration, and a phoneme sequence that is processed by a signal generation unit of the back-end subsystem. The signal generation unit includes the neural network interacting with a pre-existing knowledgebase of phenomes to generate audible speech from the input vectors. The technique applies an error signal from the neural network to correct imperfections of the pre-existing knowledgebase of phenomes to generate audible speech signals. A back-end training system is configured to train the signal generation unit by applying psychoacoustic principles to improve quality of the generated audible speech signals.

Claim (Index 17):
The method of training TTS processing of  claim 11  further comprising:\n determining a quality indicator based on audible errors; and \n ignoring inaudible errors using the psychoacoustic processing.

Metadata:
- Claim Count in Document: 29.0
- Percentile: 94.0
- Lexical Diversity: 2.1039
- Patent Class: 704.0
- Transitional Phrase Type: open
- Component Type: 1
- Foreign Priority: False
- Related Applications: ['15982326', '15203761', '15203758', '10061078', '15249457']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.2781817570705325
- 35 USC 102 Novelty (BERT): 0.5874757129723922
- Combined Prediction Score: 0.3091111526607185
- Mean Citation Score: 304.627026
- Max Citation Score: 578.8309
- Similarity Product: 408.7735922716082

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

Dataset: test