Real-Time Pitch/F0 Detection Using Spectrogram Images and Convolutional Neural Networks
Fuente:
arXiv
Gespeichert in:
| Hauptverfasser: | , |
|---|---|
| Format: | Preprint |
| Veröffentlicht: |
2025
|
| Schlagworte: | |
| Online-Zugang: | |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| _version_ | 1866916679344193536 |
|---|---|
| author | Zhao, Xufang Tsimhoni, Omer |
| author_facet | Zhao, Xufang Tsimhoni, Omer |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2504_06165 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Real-Time Pitch/F0 Detection Using Spectrogram Images and Convolutional Neural Networks Zhao, Xufang Tsimhoni, Omer Sound Artificial Intelligence Audio and Speech Processing 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. |
| title | Real-Time Pitch/F0 Detection Using Spectrogram Images and Convolutional Neural Networks |
| topic | Sound Artificial Intelligence Audio and Speech Processing |
| url | https://arxiv.org/abs/2504.06165 |