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Computer Science > Sound

Title: CONTUNER: Singing Voice Beautifying with Pitch and Expressiveness Condition

Abstract: Singing voice beautifying is a novel task that has application value in people's daily life, aiming to correct the pitch of the singing voice and improve the expressiveness without changing the original timbre and content. Existing methods rely on paired data or only concentrate on the correction of pitch. However, professional songs and amateur songs from the same person are hard to obtain, and singing voice beautifying doesn't only contain pitch correction but other aspects like emotion and rhythm. Since we propose a fast and high-fidelity singing voice beautifying system called ConTuner, a diffusion model combined with the modified condition to generate the beautified Mel-spectrogram, where the modified condition is composed of optimized pitch and expressiveness. For pitch correction, we establish a mapping relationship from MIDI, spectrum envelope to pitch. To make amateur singing more expressive, we propose the expressiveness enhancer in the latent space to convert amateur vocal tone to professional. ConTuner achieves a satisfactory beautification effect on both Mandarin and English songs. Ablation study demonstrates that the expressiveness enhancer and generator-based accelerate method in ConTuner are effective.
Comments: Accepted by the 2024 International Joint Conference on Neural Networks (IJCNN 2024)
Subjects: Sound (cs.SD); Audio and Speech Processing (eess.AS)
Cite as: arXiv:2404.19187 [cs.SD]
  (or arXiv:2404.19187v1 [cs.SD] for this version)

Submission history

From: Pengcheng Li [view email]
[v1] Tue, 30 Apr 2024 01:27:12 GMT (370kb,D)

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