在微控制器上实现低功耗实时降噪，提升嘈杂环境中的语音清晰度。
SONIC: Sound Optimization for Noise In Crowds
- 基于LMS自适应滤波，在STM32H753ZI芯片上实现嵌入式降噪。
- 实测表明语音可懂度显著提升，且满足实时性要求。
- 适合资源受限场景，替代复杂高功耗的AI降噪方案。
本文提出SONIC，一种基于ARM Cortex-M7架构的STM32H753ZI微控制器实现的嵌入式实时噪声抑制系统。采用自适应滤波（LMS）方法，有效提升嘈杂环境中的语音可懂度。研究聚焦于传统主动降噪（ANC）系统的局限性，从微控制器角度评估多种信号处理算法，分析性能因素并确定最优配置。详细阐述了系统架构设计，说明如何高效利用MCU资源，并深入解析音频信号在处理器内的转换过程。实验结果表明，该系统在保持低功耗的同时实现良好语音清晰度和实用的实时性能，证明低功耗数字信号处理是复杂AI降噪方法的可行替代方案。
原文摘要 · Abstract (English)
This paper presents SONIC, an embedded real-time noise suppression system implemented on the ARM Cortex-M7-based STM32H753ZI microcontroller. Using adaptive filtering (LMS), the system improves speech intelligibility in noisy environments. SONIC focuses on a novel approach to noise suppression in audio signals, specifically addressing the limitations of traditional Active Noise Cancellation (ANC) systems. The paper explores various signal processing algorithms in a micro-controller point of view, highlighting various performance factors and which were considered optimal in our embedded system. Additionally we also discussed the system architecture, explaining how the MCU's efficiency was harnessed, along with an in-depth overview of how the audio signals were translated within the processor. The results demonstrate improved speech clarity and practical real-time performance, showing low-power DSP as an alternative to complex AI denoising methods.
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