Time-varying Time-Frequency Tilings Using Non-Uniform Orthogonal Filterbanks Based on Mdct Analysis/synthesis and Tdar

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This invention provides an improved method and audio processor for analyzing and reconstructing audio signals using time-varying, non-uniform orthogonal filterbanks based on a modified discrete cosine transform (MDCT) and enhanced time-domain aliasing reduction (TDAR). By introducing a new technique—Switched Time Domain Aliasing Reduction (STDAR)—the system allows robust propagation between audio frames even when those frames use different time-frequency tilings. This supports more flexible, adaptive, and efficient audio coding while maintaining high audio quality, by effectively reducing undesirable aliasing and maintaining compact impulse responses during changes in signal characteristics (such as during transients or rapid changes in the audio signal).

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• Audio coding/compression (e.g., music streaming or digital audio broadcasting) where adaptive time-frequency scaling is needed for variable audio content.
• High-resolution audio or lossless/lossy audio codecs benefiting from enhanced time-frequency flexibility and improved signal reconstruction.
• Real-time audio signal processing (e.g., professional audio editing, mixing, or mastering software) that requires rapid adaptation to audio transients while retaining quality.
• Voice and speech transmission systems (such as VoIP and teleconferencing) able to adapt to dynamic signal changes for clearer communication.
• Hearing aids or audio playback devices that must manage a wide variety of sources and require minimal time and frequency artifacts.
• Multi-channel audio coding (like surround sound) where channel correlation, flexibility, and quality are critical.
• Audio analysis tools for music information retrieval, watermarking, and content recognition.

BenefitsContent extracted from patent full text and abstract with AI.

• Allows aliasing reduction between audio frames with different time-frequency tilings, enabling highly adaptive signal processing for variable content.
• Enables higher audio coding efficiency and improved perceptual audio quality, even during rapid signal changes or transients.
• Maintains compactness of both time and frequency impulse responses, minimizing audio artifacts and enhancing fidelity.
• Flexible support for non-uniform filterbanks and subband merging, adapting to diverse bandwidth and time-resolution needs without redundancy increase.
• Reduces implementation complexity—only adds a post-processing stage to common MDCT pipelines and can be efficiently coded into a bitstream.
• Compatible with joint channel processing methods, improving efficiency for multi-channel audio systems.
• Supports precise reconstruction, keeping audio quality intact across adaptive transitions.
• Reduces potential for pre-echo or other splitting/joining artifacts, leading to cleaner audio output.

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Patent Abstract

Embodiments provide a method for processing an audio signal to obtain a subband representation of the audio signal. The method comprises a step of performing a cascaded lapped critically sampled transform on at least two partially overlapping blocks of samples of the audio signal, to obtain sets of subband samples on the basis of a first block of samples of the audio signal, and to obtain sets of subband samples on the basis of a second block of samples of the audio signal. Further, the method comprises a step of identifying, in case that the sets of subband samples that are based on the first block of samples represent different regions in a time-frequency plane compared to the sets of subband samples that are based on the second block of samples, one or more sets of subband samples out of the sets of subband samples that are based on the first block of samples and one or more sets of subband samples out of the sets of subband samples that are based on the second block of samples that in combination represent the same region of the time-frequency plane. Further, the method comprises a step of performing time-frequency transforms on the identified one or more sets of subband samples out of the sets of subband samples that are based on the first block of samples and/or the identified one or more sets of subband samples out of the sets of subband samples that are based on the second block of samples, to obtain one or more time-frequency transformed subband samples, each of which represents the same region in the time-frequency plane than a corresponding one of the identified one or more subband samples or one or more time-frequency transformed versions thereof. Further, the method comprises a step of performing a weighted combination of two corresponding sets of subband samples or time-frequency transformed versions thereof, one obtained on the basis of the first block of samples of the audio signal and one obtained on the basis of the second block of samples of the audio signal, to obtain aliasing reduced subband representations of the audio signal.