PATENT CLAIM ANALYSIS

Application Number: 16197645
Application Type: Utility
Filing Date: 2018-11
Publication Date: 2019-03
Patent Classification: ["704", "500000"]

Abstract:
Provided are methods, systems, and apparatus for hierarchical decorrelation of multichannel audio. A hierarchical decorrelation algorithm is designed to adapt to possibly changing characteristics of an input signal, and also preserves the energy of the original signal. The algorithm is invertible in that the original signal can be retrieved if needed. Furthermore, the proposed algorithm decomposes the decorrelation process into multiple low-complexity steps. The contribution of these steps is generally in a decreasing order, and thus the complexity of the algorithm can be scaled.

Claim (Index 11):
A non-transitory computer-readable storage medium containing instructions that when executed cause a system to:\n segment an audio signal that includes a plurality of channels into frames; estimate, for each frame, a signal model; perform hierarchical decorrelation using the audio signal and the signal model for each of the frames to produce a plurality of decorrelated channels, wherein performing the hierarchical decorrelation includes:\n selecting a set of channels, of the plurality of channels of the audio signal, based on minimizing remaining correlation across the plurality of channels, and \n performing a unitary transform on the selected set of channels, yielding a set of decorrelated channels; \n reorder the plurality of decorrelated channels based on energy of each decorrelated channel; and combine the frames to obtain a source separated version of the audio signal.

Metadata:
- Claim Count in Document: 35.0
- Percentile: 98.0
- Lexical Diversity: 1.64912
- Patent Class: 704.0
- Transitional Phrase Type: none
- Component Type: 0
- Foreign Priority: False
- Related Applications: ['15182751', '13655225', '14767279', '14766371', '10911067']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.3385674676920731
- 35 USC 102 Novelty (BERT): 0.5697725004667885
- Combined Prediction Score: 0.3616879709695446
- Mean Citation Score: 330.418878
- Max Citation Score: 473.54697
- Similarity Product: 393.35516442505

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