Hybrid Audio Encoding for Target Bit Rate Streaming
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Solution Overview
Problem
Lossless audio coding algorithms are impractical for real-time streaming due to their unpredictable and often excessive bit rate, particularly in wireless communications where power consumption and complexity are limited, making it difficult to stream audio data in a lossless or near-lossless format over bandwidth-restricted channels.
Innovation Solution
An audio encoder that selectively applies quantization methods based on dynamic range and bit allocation, switching to lossy coding when necessary, to achieve a target bit rate, allowing for hybrid lossless/lossy coding and real-time adjustments to ensure optimal performance in various scenarios.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If lossless audio coding algorithms are used, then audio quality is improved, but bit rate becomes undeterminable and excessive
Solution Approach 1:
The encoder dynamically adjusts the coding mode between lossless and lossy based on buffer status and channel conditions. The system transitions from a static lossless coding approach to a dynamic hybrid approach, allowing the coding mode to adapt in real-time to available bandwidth and buffer capacity, thereby controlling bit rate while maintaining audio quality when possible.
Solution Approach 2:
The system changes the coding parameter (lossless vs. lossy mode) based on buffer fullness and channel bandwidth. When the buffer is not full and bandwidth permits, lossless coding is used; when the buffer is full or bandwidth is limited, the system switches to lossy coding with adjusted bit rates, thus adapting the parameter to resolve the contradiction between quality and bit rate.
2Measurement precision
If lossless audio coding is used, then audio quality is improved, but device complexity and power consumption increase
Solution Approach 1:
The encoder implements dynamic mode switching between lossless and lossy coding based on real-time buffer status and channel conditions. This dynamic adaptation reduces the average computational complexity by using simpler lossy coding when buffer conditions permit, while reserving complex lossless coding only when necessary to maintain audio quality.
Solution Approach 2:
The system changes the coding parameter (lossless vs. lossy mode) based on buffer fullness and channel bandwidth. When the buffer is not full and bandwidth permits, lossless coding is used; when the buffer is full or bandwidth is limited, the system switches to lossy coding with adjusted bit rates, thus adapting the parameter to resolve the contradiction between quality and bit rate.
3Quantity of substance
If quantization is applied to reduce bit rate, then bandwidth consumption is reduced, but audio quality deteriorates
Solution Approach 1:
The hybrid encoder applies different coding strategies to different portions of the audio signal based on their importance. Critical audio components are encoded losslessly to maintain quality, while less critical components undergo quantization to reduce bit rate. This local differentiation resolves the contradiction by applying quality-preserving coding only where necessary.
Solution Approach 2:
Instead of applying full lossless coding to the entire audio signal (excessive action), the system applies partial lossless coding only to critical components when buffer conditions permit. When the buffer is full, the system applies partial lossy coding to non-critical components, thus using just enough quantization to control bit rate while preserving essential audio quality.
4Measurement precision
If buffer size is increased to accommodate lossless coding, then audio quality is maintained, but latency increases
Solution Approach 1:
The system dynamically adjusts buffer size and coding mode based on real-time channel conditions and latency requirements. When latency is critical and buffer space is limited, the system switches to lossy coding with smaller buffers. When latency constraints are relaxed and buffer space is available, it transitions to lossless coding with larger buffers, thus dynamically resolving the contradiction between quality and latency.
Solution Approach 2:
The system changes the buffer size parameter and coding mode based on channel bandwidth and latency requirements. When the channel can support higher bit rates and latency is not critical, larger buffers are used with lossless coding. When bandwidth is limited or low latency is required, smaller buffers are used with lossy coding, thus adapting the parameter to resolve the contradiction.
Data Source
AI summary
An audio coding system in which a plurality of quantization methods are selectable for application to components of a streamed audio signal to achieve a target frame size that is determined by comparing an achieved bit rate against a target bit rate. Based on the target frame size, the system calculates a bit allocation for signal components and compares the bit allocation to the dynamic range of the signal components. Depending on the outcome of the comparison, the system may select to quantize or not quantize a signal component. The system employs lossless coding techniques, but is capable of introducing lossy coding by quantization in order to meet the target bit rate.