PATENT CLAIM ANALYSIS

Application Number: 15871918
Application Type: Utility
Filing Date: 2018-01
Publication Date: 2019-07
Patent Classification: ["704", "232000"]

Abstract:
Methods of encoding voice data for loading into an artificial intelligence (AI) integrated circuit are provided. The AI integrated circuit may have an embedded cellular neural network for implementing AI tasks based on the loaded voice data. An encoding method may generate a two-dimensional (2D) frequency-time array from an audio waveform, use the 2D frequency-time array to generate a set of 2D arrays to approximate the 2D frequency-time array, load the set of 2D arrays into the AI integrated circuit, execute programming instructions contained in the AI integrated circuit to feed the set of 2D arrays into the embedded cellular neural network in the AI integrated circuit to generate a voice recognition result, and output the voice recognition result. The encoding method also trains a convolution neural network (CNN) and loads the weights of the CNN into the AI integrated circuit for implementing the AI tasks.

Claim (Index 8):
The method of  claim 5 , wherein generating the set of 2D arrays comprises, for each pixel in the 2D frequency-time array:\n generating a sequence of random values, wherein an average of the random values in the sequence is approximate to the value of the pixel; and using the sequence of random values to determine the values of the corresponding pixels in each of the set of 2D arrays.

Metadata:
- Claim Count in Document: 49.0
- Percentile: 86.0
- Lexical Diversity: 2.42424
- Patent Class: 704.0
- Transitional Phrase Type: none
- Component Type: 0
- Foreign Priority: False
- Related Applications: ['15871933', '15871945', '14253861', '15701543', '14739335']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.2398158116194072
- 35 USC 102 Novelty (BERT): 0.5605707354611901
- Combined Prediction Score: 0.2718913040035855
- Mean Citation Score: 229.348222
- Max Citation Score: 432.32553
- Similarity Product: 328.7790104994106

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

Dataset: test