# Real-Time Pitch/F0 Detection Using Spectrogram Images and Convolutional Neural Networks

arXiv: https://arxiv.org/abs/2504.06165 · HTML: https://mlsanity.com/paper/2504.06165/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 3 of its 16 references that are in the map.
- First posted on arXiv 8 Apr 2025.

## Builds on (most cited first, 3 of 3)

- [CREPE: A Convolutional Representation for Pitch Estimation](https://mlsanity.com/paper/1802.06182/) (2018)
- [SPICE: Self-supervised Pitch Estimation](https://mlsanity.com/paper/1910.11664/) (2019)
- [A Fast and Accurate Pitch Estimation Algorithm Based on the Pseudo Wigner-Ville Distribution](https://mlsanity.com/paper/2210.15272/) (2022)

## Abstract (arXiv)

This paper presents a novel approach to detect F0 through Convolutional Neural Networks and image processing techniques to directly estimate pitch from spectrogram images. Our new approach demonstrates a very good detection accuracy; a total of 92% of predicted pitch contours have strong or moderate correlations to the true pitch contours. Furthermore, the experimental comparison between our new approach and other state-of-the-art CNN methods reveals that our approach can enhance the detection rate by approximately 5% across various Signal-to-Noise Ratio conditions.