PATENT CLAIM ANALYSIS

Application Number: 15997539
Application Type: Utility
Filing Date: 2018-06
Publication Date: 2018-10
Patent Classification: ["704", "200100"]

Abstract:
A numerical sound synthesis method for representing data as audio for use in data sonification employing a Hilbert Space eigenfunction model of human auditory perception is described. The synthesis method comprises approximating an eigenfunction equation representing a model of human hearing, calculating the approximation to each of a plurality of eigenfunctions from at least one aspect of the eigenfunction equation, and storing the approximation to each of a plurality of eigenfunctions. The approximation to each of a plurality of eigenfunctions represents a perception-oriented basis functions for mathematically representing audio information in a Hilbert-space representation of an audio signal space. The model of human hearing can include a bandpass operation with a bandwidth having the frequency range of human hearing and a time-limiting operation approximating the time duration correlation window of human hearing. In an embodiment, the approximated eigenfunctions comprise a convolution of a prolate spheroidal wavefunction with a trigonometric function.

Claim (Index 5):
The method of  claim 1 , wherein the retrieved approximations associated with each of the plurality of eigenfunctions is a numerical approximation of a particular eigenfunction.

Metadata:
- Claim Count in Document: 4.0
- Percentile: 94.0
- Lexical Diversity: 1.95062
- Patent Class: 704.0
- Transitional Phrase Type: none
- Component Type: 0
- Foreign Priority: False
- Related Applications: ['14089605', '15469429', '12849013', '14176000', '15585702']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.3645498068671699
- 35 USC 102 Novelty (BERT): 0.7044054305621393
- Combined Prediction Score: 0.3985353692366669
- Mean Citation Score: 503.948868
- Max Citation Score: 750.96765
- Similarity Product: 739.308665889457

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