Audio Signal Processing Method for Noise Reduction
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Solution Overview
Problem
Conventional audio encoding/decoding algorithms introduce significant quantization noises and man-made noises due to limited bit allocation and inaccurate quantization processes, leading to poor signal quality, especially in ADPCM and band spreading methods.
Innovation Solution
A method that processes audio signals by obtaining energy average values for each sub-band, calculating modification coefficients based on spectral envelopes and energy averages, and applying weighted modification coefficients to smooth the spectral envelopes across frames, thereby reducing noise and improving signal quality.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If multiple sub-blocks are used for parallel processing to improve decoding speed, then productivity increases, but device complexity increases due to multiple buffer memory areas and synchronization mechanisms
Solution Approach 1:
The buffer memory is segmented into multiple buffer areas (first buffer area, second buffer area, third buffer area) that are selectively activated based on the number of sub-blocks. This allows the system to scale memory resources dynamically with processing requirements, improving decoding speed while avoiding unnecessary complexity when fewer sub-blocks are used.
Solution Approach 2:
The buffer memory structure is made dynamic through selective activation of different buffer areas based on the parallel processing configuration. The system can adaptively enable or disable specific buffer areas and their associated synchronization mechanisms, allowing the device complexity to match the actual productivity requirements.
2Productivity
If multiple sub-blocks are used for parallel processing to improve decoding speed, then productivity increases, but device complexity increases due to synchronization control mechanisms
Solution Approach 1:
A buffer control unit is introduced as an intermediary component that manages synchronization between multiple sub-blocks. This centralized controller handles the complex coordination tasks, allowing individual sub-blocks to focus on their decoding operations while the control unit manages the synchronization signals and buffer area activation, thus improving productivity without proportionally increasing overall system complexity.
Solution Approach 2:
The synchronization control mechanism uses feedback from the decoding progress and buffer status to dynamically adjust the activation of buffer areas and coordination between sub-blocks. This feedback-based control allows the system to optimize the balance between productivity and complexity by activating synchronization mechanisms only when and where needed.
Data Source
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AI summary
A method and an apparatus for processing a signal are provided. The method includes: obtaining an energy average value of each sub-band for a current frame frequency-domain signal; obtaining a current frame modification coefficient of each sub-band for the current frame frequency-domain signal according to a spectral envelope and the energy average value of each sub-band; obtaining a weighted modification coefficient of each sub-band for the current frame frequency-domain signal by using the current frame modification coefficient and a relevant frame modification coefficient; and modifying the spectral envelope of each sub-band for the current frame frequency-domain signal by using the weighted modification coefficient.