Authors

* External authors

Venue

Date

Share

VRDMG: Vocal Restoration via Diffusion Posterior Sampling with Multiple Guidance

Carlos Hernandez-Olivan*

Koichi Saito

Naoki Murata

Chieh-Hsin Lai

Marco A. Martínez-Ramírez

Wei-Hsiang Liao

Yuki Mitsufuji

* External authors

ICASSP 2024

2023

Abstract

Restoring degraded music signals is essential to enhance audio quality for downstream music manipulation. Recent diffusion-based music restoration methods have demonstrated impressive performance, and among them, diffusion posterior sampling (DPS) stands out given its intrinsic properties, making it versatile across various restoration tasks. In this paper, we identify that there are potential issues which will degrade current DPS-based methods' performance and introduce the way to mitigate the issues inspired by diverse diffusion guidance techniques including the RePaint (RP) strategy and the Pseudoinverse-Guided Diffusion Models (ΠGDM). We demonstrate our methods for the vocal declipping and bandwidth extension tasks under various levels of distortion and cutoff frequency, respectively. In both tasks, our methods outperform the current DPS-based music restoration benchmarks. We refer to \url{this http URL} for examples of the restored audio samples.

Related Publications

PaGoDA: Progressive Growing of a One-Step Generator from a Low-Resolution Diffusion Teacher

NeurIPS, 2024
Dongjun Kim*, Chieh-Hsin Lai, Wei-Hsiang Liao, Yuhta Takida, Naoki Murata, Toshimitsu Uesaka, Yuki Mitsufuji, Stefano Ermon*

To accelerate sampling, diffusion models (DMs) are often distilled into generators that directly map noise to data in a single step. In this approach, the resolution of the generator is fundamentally limited by that of the teacher DM. To overcome this limitation, we propose …

GenWarp: Single Image to Novel Views with Semantic-Preserving Generative Warping

NeurIPS, 2024
Junyoung Seo, Kazumi Fukuda, Takashi Shibuya, Takuya Narihira, Naoki Murata, Shoukang Hu, Chieh-Hsin Lai, Seungryong Kim*, Yuki Mitsufuji

Generating novel views from a single image remains a challenging task due to the complexity of 3D scenes and the limited diversity in the existing multi-view datasets to train a model on. Recent research combining large-scale text-to-image (T2I) models with monocular depth e…

The whole is greater than the sum of its parts: improving music source separation by bridging networks

EURASIP, 2024
Ryosuke Sawata, Naoya Takahashi, Stefan Uhlich*, Shusuke Takahashi*, Yuki Mitsufuji

This paper presents the crossing scheme (X-scheme) for improving the performance of deep neural network (DNN)-based music source separation (MSS) with almost no increasing calculation cost. It consists of three components: (i) multi-domain loss (MDL), (ii) bridging operation…

  • HOME
  • Publications
  • VRDMG: Vocal Restoration via Diffusion Posterior Sampling with Multiple Guidance

JOIN US

Shape the Future of AI with Sony AI

We want to hear from those of you who have a strong desire
to shape the future of AI.