PATENT CLAIM ANALYSIS

Application Number: 15924963
Application Type: Utility
Filing Date: 2018-03
Publication Date: 2018-07
Patent Classification: ["704", "500000"]

Abstract:
An autocorrelation calculating part calculates autocorrelation R o (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 R o (i) by a coefficient w o (i). Here, a case is comprised where, for at least part of each order i, the coefficient w o (i) corresponding to each order i monotonically decreases as a value having positive correlation with a pitch gain in an input signal of a current frame or a past frame increases.

Claim (Index 3):
A linear predictive analysis apparatus which obtains 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 apparatus comprising:\n processing circuitry configured to\n calculate 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 max ; and \n obtain 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 for each corresponding i, \n wherein the processing circuitry is further configured to acquire the coefficient from one coefficient table among coefficient tables t 0 , t 1  and t 2  using a value having positive correlation with intensity of periodicity of an input time series signal of the current frame or a past frame or a pitch gain based on the input time series signal assuming that a coefficient w t0 (i) is stored in the coefficient table t 0 , a coefficient w t1 (i) is stored in the coefficient table t 1 , and a coefficient w t2 (i) is stored in the coefficient table t 2 , \n assuming that, according to the value having positive correlation with the intensity of the periodicity or the pitch gain, a case is classified into any of a case where the intensity of the periodicity or the pitch gain is high, a case where the intensity of the periodicity or the pitch gain is medium and a case where the intensity of the periodicity or the pitch gain is low, a coefficient table from which a coefficient is acquired by the processing circuitry when the intensity of the periodicity or the pitch gain is high is set as a coefficient table t 0 , a coefficient table from which a coefficient is acquired by the processing circuitry when the intensity of the periodicity or the pitch gain is medium is set as a coefficient table t 1 , and a coefficient table from which a coefficient is acquired by the processing circuitry when the intensity of the periodicity or the pitch gain is low is set as a coefficient table t 2 , for at least part of i other than i=0, w t0 (i)<w t1 (i)\u2264w t2 (i), for at least part of each i among other i other than i=0, w t0 (i)\u2264w t1 (i)<w t2 (i), and for the remaining each i other than i=0, w t0 (i)\u2264w t1 (i)\u2264w t2 (i).

Metadata:
- Claim Count in Document: 9.0
- Percentile: 90.0
- Lexical Diversity: 1.78333
- Patent Class: 704.0
- Transitional Phrase Type: open
- Component Type: 1
- Foreign Priority: True
- Related Applications: ['15889748', '15889775', '15924887', '15112534', '15112318']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.3585038626455872
- 35 USC 102 Novelty (BERT): 0.5695177813420029
- Combined Prediction Score: 0.3796052545152288
- Mean Citation Score: 436.803906
- Max Citation Score: 453.8736
- Similarity Product: 446.9119498083115

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