Audio Signal Compression Using Zero-Crossing Peak Scaling
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Solution Overview
Problem
Existing audio signal compression systems either introduce distortion by reducing the signal level too late or incur noise and inefficiency by not utilizing the full dynamic range, as they often rely on peak detection methods that are prone to errors and ambiguity.
Innovation Solution
A method that identifies zero crossing points in audio signals to buffer and analyze half-waves, scaling samples to prevent peak values from exceeding a threshold, using an initial scaling factor and a decay factor to adjust subsequent half-waves, ensuring that all samples remain within the threshold without distorting the waveform.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If peak detection methods are used to control audio signal level, then the signal level can be reduced when exceeding threshold, but distortion is introduced because the procedure occurs too late
Solution Approach 1:
The patent applies preliminary action by identifying zero crossing points and buffering samples before the peak occurs. The system stores samples in a buffer until a zero crossing is detected, then analyzes the buffered samples to determine the appropriate scaling factor in advance, allowing the signal to be scaled before peaks exceed the threshold, thereby preventing distortion rather than correcting it after the fact.
2Reliability
If additional headroom is provided for the input signal, then peak values remain within dynamic range, but noise and inefficiency increase due to unavailable full dynamic range
Solution Approach 1:
The patent applies dynamics by implementing a dynamic scaling mechanism that adjusts the scaling factor based on the actual signal characteristics. Instead of providing fixed headroom, the system calculates an initial scaling factor from buffered samples and applies it dynamically. The decay factor further refines this dynamically, allowing the system to utilize the full dynamic range efficiently while still preventing peaks from exceeding the threshold, thus avoiding the noise and inefficiency associated with fixed headroom approaches.
3Productivity
If the full dynamic range is utilized, then efficiency is improved, but the risk of distortion increases when peak values exceed the threshold
Solution Approach 1:
The patent applies feedback by continuously monitoring the signal and using the identified peak value from buffered samples to determine the scaling factor. The system calculates the initial scaling factor based on the peak detection from buffered samples, then applies this scaling factor to scale the signal appropriately. This feedback mechanism ensures that the full dynamic range is utilized efficiently while preventing distortion by adjusting the signal level based on actual peak values.
Data Source
AI summary
An audio signal in which an audio signal is received as a stream of digital samples, each being a numerical value representing a sampled signal level. A first zero crossing point is identified and the received audio samples are stored until a second zero crossing point is identified, thereby storing a first half-wave of samples. The highest intensity sample is identified from the stored samples and this is compared against a predetermined threshold. All stored samples are scaled by an initial scaling factor so that the intensity of the highest intensity sample is not above this threshold. A second half-wave of samples is stored in which all samples of the second half-wave are below the threshold. All stored samples of the second half-wave are also scaled but by a modified scaling factor derived from a combination of the initial scaling factor and a decay factor.