FCPE: A Fast Context-based Pitch Estimation Model

• URL: http://arxiv.org/abs/2509.15140v1
• Date: Thu, 18 Sep 2025 16:50:09 GMT
• Title: FCPE: A Fast Context-based Pitch Estimation Model
• Authors: Yuxin Luo, Ruoyi Zhang, Lu-Chuan Liu, Tianyu Li, Hangyu Liu,
• Abstract summary: We propose a fast context-based pitch estimation model that captures mel spectrogram features while maintaining low computational cost and robust noise tolerance.<n>Experiments show that our method achieves 96.79% Raw Pitch Accuracy (RPA) on the MIR-1K dataset, on par with the state-of-the-art methods.
• Score: 10.788664167503676
• License: http://creativecommons.org/licenses/by-nc-sa/4.0/
• Abstract: Pitch estimation (PE) in monophonic audio is crucial for MIDI transcription and singing voice conversion (SVC), but existing methods suffer significant performance degradation under noise. In this paper, we propose FCPE, a fast context-based pitch estimation model that employs a Lynx-Net architecture with depth-wise separable convolutions to effectively capture mel spectrogram features while maintaining low computational cost and robust noise tolerance. Experiments show that our method achieves 96.79\% Raw Pitch Accuracy (RPA) on the MIR-1K dataset, on par with the state-of-the-art methods. The Real-Time Factor (RTF) is 0.0062 on a single RTX 4090 GPU, which significantly outperforms existing algorithms in efficiency. Code is available at https://github.com/CNChTu/FCPE.

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