Audio Signal Decoding With Temporal Mismatch Compensation
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Solution Overview
Problem
Existing audio decoding technologies face challenges in reducing the difference between output signals and original audio signals in limited communication bandwidth, particularly in scenarios with temporal shifts and phase mismatches between audio channels.
Innovation Solution
The system employs an encoder to determine temporal mismatch values between audio signals from multiple microphones, adjusts the encoding process by selecting a reference and target signal, and generates encoded mid and side signals based on these values, optimizing bit allocation to minimize bandwidth usage while maintaining audio quality.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of energy
If standard audio encoding is used to transmit audio signals over limited bandwidth, then bandwidth consumption is reduced, but the difference between output signals and original audio signals increases
Solution Approach 1:
The audio signal is segmented into mid signal and side signal components, which are then encoded separately. This segmentation allows for more efficient bandwidth utilization while preserving the essential characteristics of the original audio signal, thereby reducing the difference between output and original signals under limited bandwidth conditions.
Solution Approach 2:
Temporal mismatch values and inter-channel prediction gain parameters are calculated in advance during the encoding process. These pre-computed parameters are then used to guide the decoding process, enabling the receiver to reconstruct the audio signal more accurately with fewer transmitted data elements, thus reducing bandwidth consumption without sacrificing audio quality.
2Manufacturing precision
If temporal mismatch compensation is implemented to reduce phase mismatches between audio channels, then audio quality is improved, but encoding complexity increases
Solution Approach 1:
The encoder dynamically adjusts encoding parameters based on calculated temporal mismatch values and inter-channel prediction gain. By changing parameters such as bit allocation and prediction strength according to the measured temporal characteristics, the system achieves improved audio quality without requiring complex real-time processing, thus managing encoding complexity effectively.
3Productivity
If dynamic bit allocation is used to optimize bandwidth usage, then network resource efficiency is improved, but decoding complexity increases
Solution Approach 1:
The encoding process incorporates feedback mechanisms where temporal mismatch values and inter-channel prediction gain parameters are calculated and used to dynamically adjust bit allocation. These feedback-driven parameter adjustments enable efficient bandwidth usage while the pre-computed nature of the parameters keeps the decoding complexity manageable, as the decoder simply needs to apply the received parameters rather than perform complex real-time calculations.
Data Source
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AI summary
A device includes a receiver and a decoder. The receiver is configured to receive bitstream parameters corresponding to at least an encoded mid signal. The decoder is configured to generate a synthesized mid signal based on the bitstream parameters. The decoder is also configured to generate a synthesized side signal selectively based on the bitstream parameters in response to determining whether the bitstream parameters correspond to an encoded side signal.