Audio Decoder Frequency Tile Adaptation for Artifact Reduction
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Solution Overview
Problem
Current audio codecs face challenges in maintaining perceptual quality at low bitrates due to limitations in bandwidth extension techniques, which result in loss of high-frequency detail and timbre, and introduce artifacts like dissonance and warbling, especially in transform-based implementations.
Innovation Solution
The proposed solution involves a signal-adaptive approach for decoding audio signals, where a decoder-side analysis detects tonal components and adjusts frequency borders to minimize splitting and beating artifacts, and applies cross-over filtering to reduce ringing, allowing for more accurate spectral regeneration and improved perceptual quality.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If bandwidth extension techniques are used to maintain audio quality at low bitrates, then compression efficiency is improved, but high-frequency detail and timbre are lost
Solution Approach 1:
The frequency spectrum is divided into multiple frequency tiles, with different spectral resolutions assigned to different regions. High-frequency regions use coarser resolution for compression, while low-frequency regions maintain finer resolution to preserve detail and timbre.
Solution Approach 2:
Different spectral resolutions are applied to different frequency regions based on their importance. Critical low-frequency regions retain high spectral resolution for accurate timbre representation, while less critical high-frequency regions use lower resolution to achieve compression.
2Productivity
If bandwidth extension techniques are used to extend audio bandwidth at low bitrates, then compression efficiency is improved, but artifacts like dissonance and warbling are introduced
Solution Approach 1:
Frequency borders between spectral tiles are made adaptive rather than fixed. The decoder analyzes the decoded core signal and adjusts frequency borders dynamically to avoid splitting tonal components, thereby preventing dissonance and warbling artifacts while maintaining compression efficiency.
Solution Approach 2:
The system employs a feedback mechanism where the decoded core signal is analyzed to detect tonal components, and this information is used to adaptively adjust frequency borders before spectral regeneration, preventing artifact generation.
3Device complexity
If fixed frequency borders are used in spectral regeneration, then device complexity is reduced, but tonal components are split causing dissonance artifacts
Solution Approach 1:
The frequency borders are changed from fixed to dynamic/adaptive. The system analyzes the signal content and adjusts frequency borders accordingly to prevent splitting of tonal components, eliminating dissonance artifacts while maintaining reasonable system complexity.
4Productivity
If transform-based bandwidth extension is applied, then compression efficiency is improved, but ringing artifacts occur due to abrupt frequency transitions
Solution Approach 1:
Cross-over filtering is introduced as an intermediary process between spectral tiles with different resolutions. This filtering smooths abrupt frequency transitions at boundaries, eliminating ringing artifacts while preserving the compression benefits of transform-based bandwidth extension.
Data Source
AI summary
Apparatus for decoding an encoded audio signal including an encoded core signal and parametric data, including: a core decoder for decoding the encoded core signal to obtain a decoded core signal; an analyzer for analyzing the decoded core signal before or after performing a frequency regeneration operation to provide an analysis result; and a frequency regenerator for regenerating spectral portions not included in the decoded core signal using a spectral portion of the decoded core signal, the parametric data, and the analysis result.