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 11):
The apparatus according to  claim 7 , wherein the codebook vector determiner is configured to conduct a singular value decomposition on the autocorrelation matrix R to decompose the autocorrelation matrix R to conduct the matrix decomposition to determine the diagonal matrix D for determining the codebook vector.

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): 0.2882160862412852
- 35 USC 102 Novelty (BERT): 0.609803299858055
- Combined Prediction Score: 0.3203748076029622
- Mean Citation Score: 300.373956
- Max Citation Score: 546.6558
- Similarity Product: 499.01583447557687

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