Please check whether this paper is about 'Voice Conversion' or not.
article info.
title: LHQ-SVC: Lightweight and High Quality Singing Voice Conversion Modeling
summary: Singing Voice Conversion (SVC) has emerged as a significant subfield of Voice
Conversion (VC), enabling the transformation of one singer's voice into another
while preserving musical elements such as melody, rhythm, and timbre.
Traditional SVC methods have limitations in terms of audio quality, data
requirements, and computational complexity. In this paper, we propose LHQ-SVC,
a lightweight, CPU-compatible model based on the SVC framework and diffusion
model, designed to reduce model size and computational demand without
sacrificing performance. We incorporate features to improve inference quality,
and optimize for CPU execution by using performance tuning tools and parallel
computing frameworks. Our experiments demonstrate that LHQ-SVC maintains
competitive performance, with significant improvements in processing speed and
efficiency across different devices. The results suggest that LHQ-SVC can meet
Please check whether this paper is about 'Voice Conversion' or not.
article info.
title: LHQ-SVC: Lightweight and High Quality Singing Voice Conversion Modeling
summary: Singing Voice Conversion (SVC) has emerged as a significant subfield of Voice Conversion (VC), enabling the transformation of one singer's voice into another while preserving musical elements such as melody, rhythm, and timbre. Traditional SVC methods have limitations in terms of audio quality, data requirements, and computational complexity. In this paper, we propose LHQ-SVC, a lightweight, CPU-compatible model based on the SVC framework and diffusion model, designed to reduce model size and computational demand without sacrificing performance. We incorporate features to improve inference quality, and optimize for CPU execution by using performance tuning tools and parallel computing frameworks. Our experiments demonstrate that LHQ-SVC maintains competitive performance, with significant improvements in processing speed and efficiency across different devices. The results suggest that LHQ-SVC can meet
id: http://arxiv.org/abs/2409.08583v1
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