PATENT CLAIM ANALYSIS

Application Number: 15889684
Application Type: Utility
Filing Date: 2018-02
Publication Date: 2018-06
Patent Classification: ["704", "216000"]

Abstract:
An autocorrelation calculating part calculates autocorrelation Ro(i) from an input signal. A predictive coefficient calculating part performs linear predictive analysis using modified autocorrelation R′o(i) obtained by multiplying the autocorrelation Ro(i) by a coefficient wo(i). Here, it is assumed that a case where, for at least part of each order i, the coefficient wo(i) corresponding to each order i monotonically increases as a value having negative correlation with a fundamental frequency of an input signal in a current frame or a past frame increases and a case where the coefficient wo(i) monotonically decreases as a value having positive correlation with a pitch gain in a current frame or a past frame increases, are included.

Claim (Index 2):
A linear predictive analysis method for obtaining a coefficient which can be converted into a linear predictive coefficient corresponding to an input time series signal for each frame which is a predetermined time interval, the linear predictive analysis method comprising:\n an autocorrelation calculating step of calculating autocorrelation R o (i) between an input time series signal X o (n) of a current frame and an input time series signal X o (n\u2212i) i sample before the input time series signal X o (n) or an input time series signal X o (n+i) i sample after the input time series signal X o (n) for each of at least i=0, 1, . . . , P m ; and a predictive coefficient calculating step of obtaining a coefficient which can be converted into linear predictive coefficients from the first-order to the P max -order using modified autocorrelation R\u2032 o (i) obtained by multiplying the autocorrelation R o (i) by a coefficient w o (i) corresponding to the each order for each corresponding i, wherein the linear predictive analysis method further comprises a coefficient determining step of acquiring the coefficient w o (i) from one coefficient table among two or more coefficient tables using a value having positive correlation with a fundamental frequency based on an input time series signal in the current frame or a past frame and a value having positive correlation with intensity of periodicity or a pitch gain of the input time series signal in the current frame or the past frame assuming that coefficients w o (i) are stored in each of the two or more coefficient tables, assuming that among the two or more coefficient tables, a coefficient table from which the coefficient w o (i) is acquired in the coefficient determining step when the value having positive correlation with the fundamental frequency is a first value and the value having positive correlation with the intensity of periodicity or the pitch gain is a third value is a first coefficient table, and among the two or more coefficient tables, a coefficient table from which the coefficient w o (i) is acquired in the coefficient determining step when the value having positive correlation with the fundamental frequency is a second value which is smaller than the first value and the value having positive correlation with the intensity of periodicity or the pitch gain is a fourth value which is smaller than the third value is a second coefficient table, for at least part of each order i, a coefficient corresponding to the each order i in the second coefficient table is greater than a coefficient corresponding to the each order i in the first coefficient table.

Metadata:
- Claim Count in Document: 9.0
- Percentile: 88.0
- Lexical Diversity: 2.0597
- Patent Class: 704.0
- Transitional Phrase Type: open
- Component Type: 1
- Foreign Priority: True
- Related Applications: ['15112318', '15889748', '15889775', '15112534', '12280101']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.3431979123674768
- 35 USC 102 Novelty (BERT): 0.620214851801037
- Combined Prediction Score: 0.3708996063108328
- Mean Citation Score: 439.923208
- Max Citation Score: 558.39795
- Similarity Product: 553.5649093859018

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

Dataset: test