Please check whether this paper is about 'Voice Conversion' or not.
article info.
title: LCM-SVC: Latent Diffusion Model Based Singing Voice Conversion with Inference Acceleration via Latent Consistency Distillation
summary: Any-to-any singing voice conversion (SVC) aims to transfer a target singer's
timbre to other songs using a short voice sample. However many diffusion model
based any-to-any SVC methods, which have achieved impressive results, usually
suffered from low efficiency caused by a mass of inference steps. In this
paper, we propose LCM-SVC, a latent consistency distillation (LCD) based latent
diffusion model (LDM) to accelerate inference speed. We achieved one-step or
few-step inference while maintaining the high performance by distilling a
pre-trained LDM based SVC model, which had the advantages of timbre decoupling
and sound quality. Experimental results show that our proposed method can
significantly reduce the inference time and largely preserve the sound quality
and timbre similarity comparing with other state-of-the-art SVC models. Audio
samples are available at https://sounddemos.github.io/lcm-svc.
Please check whether this paper is about 'Voice Conversion' or not.
article info.
title: LCM-SVC: Latent Diffusion Model Based Singing Voice Conversion with Inference Acceleration via Latent Consistency Distillation
summary: Any-to-any singing voice conversion (SVC) aims to transfer a target singer's timbre to other songs using a short voice sample. However many diffusion model based any-to-any SVC methods, which have achieved impressive results, usually suffered from low efficiency caused by a mass of inference steps. In this paper, we propose LCM-SVC, a latent consistency distillation (LCD) based latent diffusion model (LDM) to accelerate inference speed. We achieved one-step or few-step inference while maintaining the high performance by distilling a pre-trained LDM based SVC model, which had the advantages of timbre decoupling and sound quality. Experimental results show that our proposed method can significantly reduce the inference time and largely preserve the sound quality and timbre similarity comparing with other state-of-the-art SVC models. Audio samples are available at https://sounddemos.github.io/lcm-svc.
id: http://arxiv.org/abs/2408.12354v1
judge
Write [vclab::confirmed] or [vclab::excluded] in comment.