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CREPE: A Convolutional Representation for Pitch Estimation

arXiv 1802.06182 ↗First posted 17 Feb 2018eess.AS cs.LG cs.SDcited by 109

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Abstract (arXiv)

The task of estimating the fundamental frequency of a monophonic sound recording, also known as pitch tracking, is fundamental to audio processing with multiple applications in speech processing and music information retrieval. To date, the best performing techniques, such as the pYIN algorithm, are based on a combination of DSP pipelines and heuristics. While such techniques perform very well on average, there remain many cases in which they fail to correctly estimate the pitch. In this paper, we propose a data-driven pitch tracking algorithm, CREPE, which is based on a deep convolutional neural network that operates directly on the time-domain waveform. We show that the proposed model produces state-of-the-art results, performing equally or better than pYIN. Furthermore, we evaluate the model's generalizability in terms of noise robustness. A pre-trained version of CREPE is made freely available as an open-source Python module for easy application.

Key facts. Cited by 109 papers in the map (data through 7 Oct 2026). First posted on arXiv 17 Feb 2018.

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Citing papers per year: 2021: 14; 2022: 22; 2023: 12; 2024: 17; 2025: 25; 2026: 19.

109 papers.

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  12. 2022DDX7: Differentiable FM Synthesis of Musical Instrument Soundscited by 13
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  9. 2024DiffMoog: a Differentiable Modular Synthesizer for Sound Matchingcited by 7
  10. 2022Towards Robust Unsupervised Disentanglement of Sequential Data -- A Case Study Using Music Audiocited by 6
  11. 2022The Efficacy of Self-Supervised Speech Models for Audio Representationscited by 6
  12. 2023A multimodal dynamical variational autoencoder for audiovisual speech representation learningcited by 6
  13. 2024LDM-SVC: Latent Diffusion Model Based Zero-Shot Any-to-Any Singing Voice Conversion with Singer Guidancecited by 6
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  15. 2021RefineGAN: Universally Generating Waveform Better than Ground Truth with Highly Accurate Pitch and Intensity Responsescited by 5
  16. 2022FretNet: Continuous-Valued Pitch Contour Streaming for Polyphonic Guitar Tablature Transcriptioncited by 5
  17. 2023Real-time Detection of AI-Generated Speech for DeepFake Voice Conversioncited by 5
  18. 2024SongBsAb: A Dual Prevention Approach against Singing Voice Conversion based Illegal Song Coverscited by 5
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  25. 2022Differentiable Digital Signal Processing Mixture Model for Synthesis Parameter Extraction from Mixture of Harmonic Soundscited by 4
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  28. 2024Differentiable Modal Synthesis for Physical Modeling of Planar String Sound and Motion Simulationcited by 4
  29. 2025RT-VC: Real-Time Zero-Shot Voice Conversion with Speech Articulatory Codingcited by 4
  30. 2026Self Voice Conversion as an Attack against Neural Audio Watermarkingcited by 4
  31. 2021Latent Space Explorations of Singing Voice Synthesis using DDSPcited by 3
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  38. 2023Finding Tori: Self-supervised Learning for Analyzing Korean Folk Songcited by 3

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