PATENT CLAIM ANALYSIS

Application Number: 16123980
Application Type: Utility
Filing Date: 2018-09
Publication Date: 2019-01
Patent Classification: ["381", "022000"]

Abstract:
Multi-channel audio content is mixed for a particular loudspeaker setup. However, a consumer's audio setup is very likely to use a different placement of speakers. The present invention provides a method of rendering multi-channel audio that assures replay of the spatial signal components with equal loudness of the signal. A method for obtaining an energy preserving mixing matrix (G) for mixing L1 input audio channels to L2 output channels comprises steps of obtaining a first mixing matrix Ĝ, performing a singular value decomposition on the first mixing matrix Ĝ to obtain a singularity matrix S, processing the singularity matrix S to obtain a processed singularity matrix Ŝ, determining a scaling factor a, and calculating an improved mixing matrix G according to G=a U Ŝ V T . The perceived sound, loudness, timbre and spatial impression of multi-channel audio replayed on an arbitrary loudspeaker setup practically equals that of the original speaker setup.

Claim (Index 1):
A method for rendering L1 channel-based input audio signals to L2 loudspeaker channels, the method comprising:\n receiving information regarding a setup geometry; performing a first delay and gain compensation on the L1 channel-based input audio signals based on the setup geometry to obtain a delayed and gain compensated input audio signal; determining a remixed audio signal for the L2 loudspeaker audio channels by applying an energy preserving mixing matrix to the delayed and gain compensated input audio signal, wherein the remixed audio signal for output audio channels is further based on a second delay compensation and a second gain compensation.

Metadata:
- Claim Count in Document: 5.0
- Percentile: 97.0
- Lexical Diversity: 1.82418
- Patent Class: 381.0
- Transitional Phrase Type: open
- Component Type: 1
- Foreign Priority: True
- Related Applications: ['15457718', '14906255', '16114937', '15619935', '15920849']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.6939380840187837
- 35 USC 102 Novelty (BERT): 0.5387938707696663
- Combined Prediction Score: 0.6784236626938719
- Mean Citation Score: 256.357316
- Max Citation Score: 382.9535
- Similarity Product: 363.6930837724209

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

Dataset: test