PATENT CLAIM ANALYSIS

Application Number: 16209610
Application Type: Utility
Filing Date: 2018-12
Publication Date: 2019-04
Patent Classification: ["704", "222000"]

Abstract:
An apparatus for encoding a speech signal by determining a codebook vector of a speech coding algorithm is provided. The apparatus includes a matrix determiner for determining an autocorrelation matrix R, and a codebook vector determiner for determining the codebook vector depending on the autocorrelation matrix R. The matrix determiner is configured to determine the autocorrelation matrix R by determining vector coefficients of a vector r, wherein the autocorrelation matrix R includes a plurality of rows and a plurality of columns, wherein the vector r indicates one of the columns or one of the rows of the autocorrelation matrix R, wherein R(i, j)=r(|i−j|), wherein R(i, j) indicates the coefficients of the autocorrelation matrix R, wherein i is a first index indicating one of a plurality of rows of the autocorrelation matrix R, and wherein j is a second index indicating one of the plurality of columns of the autocorrelation matrix R.

Claim (Index 14):
The apparatus according to  claim 1 ,\n wherein the apparatus is an encoder for encoding the speech signal by employing algebraic code excited linear prediction speech coding, and wherein the codebook vector determiner is configured to determine the codebook vector based on the autocorrelation matrix R as a codebook vector of an algebraic codebook.

Metadata:
- Claim Count in Document: 5.0
- Percentile: 98.0
- Lexical Diversity: 3.30769
- Patent Class: 704.0
- Transitional Phrase Type: none
- Component Type: 0
- Foreign Priority: False
- Related Applications: ['14678610', '15256996', '13768814', '11508849', '11095605']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.2857808279001114
- 35 USC 102 Novelty (BERT): 0.616913564090771
- Combined Prediction Score: 0.3188941015191774
- Mean Citation Score: 300.373956
- Max Citation Score: 546.6558
- Similarity Product: 529.1985227470279

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

Dataset: test