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English(EN) Five Ways to Compute an STFT on a Qualcomm SoC: Accuracy, Latency, and Power, Measured Not Guessed

Qualcomm SoC:测量音频AI的STFT计算路径

本文探讨了在Qualcomm片上系统(SoC)上计算短时傅里叶变换(STFT)的五种不同方法,特别关注Snapdragon SM8650。文章详细介绍了使用CPU、专用数字信号处理器(cDSP)和神经网络处理单元(NPU)的实现方式,并测量了每种方法的精度、延迟和功耗。研究结果表明,最佳方法取决于下游音频AI管道的具体需求,而不是单一的普遍最佳方法。 AI

影响 通过比较STFT的计算路径,为优化边缘设备的音频AI管道提供数据。

排序理由 该条目详细介绍了在硬件上针对特定信号处理算法的不同计算路径的技术比较,包括方法论和实测结果。[lever_c_demoted from research: ic=1 ai=0.7]

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Qualcomm SoC:测量音频AI的STFT计算路径

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该条目详细介绍了在硬件上针对特定信号处理算法的不同计算路径的技术比较,包括方法论和实测结果。[lever_c_demoted from research: ic=1 ai=0.7]
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  1. Towards AI TIER_1 English(EN) · Gaobin ·

    高通 SoC 上计算 STFT 的五种方法:准确性、延迟和功耗,实测而非猜测

    <figure><img alt="" src="https://cdn-images-1.medium.com/max/1024/1*em2YkHd_ihXFflGb3UjPbw.png" /><figcaption>Image by Author via AI</figcaption></figure><h4><em>A field comparison of CPU, cDSP, and HTP-NPU STFT paths on Snapdragon SM8650 — and why “which one is best” is the wron…