Audio Encoding with Adaptive MDCT Blocks for Pre-Echo Control
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Solution Overview
Problem
Existing audio codec technologies fail to effectively control or eliminate pre-echo artifacts, especially noticeable in audio with sharp impulses and transient signals, due to inaccuracies during time domain to frequency domain conversion and back, leading to suboptimal sound quality in dynamic and distributed IP-based multimedia systems.
Innovation Solution
A computer-implemented system and method that encodes sampled audio signals by identifying potential pre-echo events, generating an error signal, and encoding this information into a bitstream, allowing for the removal of pre-echo artifacts during decoding, using techniques such as pulse code modulation, adaptive pulse code modulation, and modified discrete cosine transform.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If MDCT transform is used to convert time domain signal to frequency domain and back, then audio compression is achieved, but pre-echo artifacts are introduced due to error spreading across block size
Solution Approach 1:
The audio signal is divided into multiple blocks for MDCT processing, and the patent identifies specific blocks containing transient signals. By segmenting the processing approach - using different block sizes (short blocks for transients, long blocks for steady-state signals) - the patent prevents error spreading across entire long blocks, thereby reducing pre-echo artifacts while maintaining compression efficiency.
Solution Approach 2:
The patent dynamically adjusts the MDCT block size based on the detected signal characteristics. When transient signals are detected, shorter block sizes are used to minimize the temporal spread of quantization errors. For steady-state signals, longer block sizes are used to maintain compression efficiency. This dynamic adaptation resolves the contradiction between compression efficiency and pre-echo prevention.
2Quantity of substance
If quantization is applied during MDCT transformation, then bit rate reduction is achieved, but pre-echo artifacts become noticeable especially in transient signals
Solution Approach 1:
The patent applies different quantization strategies to different signal regions. For blocks containing transient signals, finer quantization or alternative processing is applied to prevent pre-echo artifacts. For blocks with steady-state signals, coarser quantization is acceptable to achieve bit rate reduction. This local differentiation allows bit rate optimization without introducing noticeable pre-echo artifacts in critical transient regions.
3Device complexity
If fixed block size MDCT is used for encoding, then encoding simplicity is maintained, but sound quality deteriorates in audio with sharp impulses and transient signals
Solution Approach 1:
The patent introduces dynamic block size selection based on transient detection in the signal. The encoder analyzes each block to determine if it contains transient content and adjusts the block size accordingly. This dynamic approach improves sound quality for transient signals while maintaining reasonable encoding complexity through automated detection and selection algorithms.
Data Source
AI summary
An encoder operable to filter audio signals into a plurality of frequency band components, generate quantized digital components for each band, identify a potential for pre-echo events within the generated quantized digital components, generate an approximate signal by decoding the quantized digital components using inverse pulse code modulation, generate an error signal by comparing the approximate signal with the sampled audio signal, and process the error signal and quantized digital components. The encoder operable to process the error signal by processing delayed audio signals and Q band values, determining the potential for pre-echo events from the Q band values, and determining scale factors and MDCT block sizes for the potential for pre-echo events. The encoder operable to transform the error signal into high resolution frequency components using the MDCT block sizes, quantize the scale factors and frequency components, and encode the quantized lines, block sizes, and quantized scale factors for inclusion in the bitstream.