MF-PAM: Accurate Pitch Estimation through Periodicity Analysis and Multi-level Feature Fusion

International Conference
2023-08-11 11:15
Authors : Woo-Jin Chung, Doyeon Kim, Soo-Whan Chung, Hong-Goo Kang

Year : 2023

Publisher / Conference : INTERSPEECH

Research area : Speech Signal Processing, Etc

Related project : 다양한 환경에 따른 왜곡 음성 신호 전처리 및 복원 알고리즘 개발

Presentation : Oral

We introduce Multi-level feature Fusion-based Periodicity Analysis Model (MF-PAM), a novel deep learning-based pitch estimation model that accurately estimates pitch trajectory in noisy and reverberant acoustic environments. Our model leverages the periodic characteristics of audio signals and involves two key steps: extracting pitch periodicity using periodic non-periodic convolution (PNP-Conv) blocks and estimating pitch by aggregating multi-level features using a modified bidirectional feature pyramid network (BiFPN). We evaluate our model on speech and music datasets and achieve superior pitch estimation performance compared to state-of-the-art baselines while using fewer model parameters. Our model achieves 99.20% accuracy in the pitch estimation on a clean musical dataset. Overall, our proposed model provides a promising solution for accurate pitch estimation in challenging acoustic environments and has potential applications in audio signal processing.
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