Pitch Estimation in Real Time: Revisiting SWIPE with Causal Windowing

Pitch estimation in real time is essential for a wide range of Music Information Retrieval (MIR) applications, including intonation monitoring, music education, and interactive systems. Many of these use cases, such as ensemble rehearsals, require low-latency, multi-channel audio processing on resource-constrained devices. While recent approaches with neural networks offer high accuracy, they often fall short in real-time performance due to computational demands. In this paper, we revisit the well-established SWIPE algorithm and introduce RT-SWIPE, a real-time variant enabled by using causal windowing. We further propose a delay-tolerant evaluation metric that extends Raw Pitch Accuracy (RPA) to account for algorithmic delays. Experimental results on synthetic signals and multi-track ensemble recordings demonstrate that RT-SWIPE provides a practical balance of latency, accuracy, and efficiency. Although our study focuses on wind orchestra scenarios, the method is broadly applicable to similar real-time settings.