Papers
arxiv:2504.06165

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

Published on Apr 8, 2025
Authors:
,

Abstract

A new Convolutional Neural Network approach accurately estimates pitch from spectrogram images, achieving strong or moderate correlation with true pitch contours and improving detection rates over existing CNN methods.

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.

Community

Sign up or log in to comment

Get this paper in your agent:

hf papers read 2504.06165
Don't have the latest CLI?
curl -LsSf https://hf.co/cli/install.sh | bash

Models citing this paper 0

No model linking this paper

Cite arxiv.org/abs/2504.06165 in a model README.md to link it from this page.

Datasets citing this paper 0

No dataset linking this paper

Cite arxiv.org/abs/2504.06165 in a dataset README.md to link it from this page.

Spaces citing this paper 0

No Space linking this paper

Cite arxiv.org/abs/2504.06165 in a Space README.md to link it from this page.

Collections including this paper 0

No Collection including this paper

Add this paper to a collection to link it from this page.