VoiceTailor: Lightweight Plug-In Adapter for Diffusion-Based Personalized Text-to-Speech

Fuente: arXiv
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Autores principales: Kim, Heeseung, Lee, Sang-gil, Yeom, Jiheum, Lee, Che Hyun, Kim, Sungwon, Yoon, Sungroh
Formato: Preprint
Publicado: 2024
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author Kim, Heeseung
Lee, Sang-gil
Yeom, Jiheum
Lee, Che Hyun
Kim, Sungwon
Yoon, Sungroh
author_facet Kim, Heeseung
Lee, Sang-gil
Yeom, Jiheum
Lee, Che Hyun
Kim, Sungwon
Yoon, Sungroh
contents We propose VoiceTailor, a parameter-efficient speaker-adaptive text-to-speech (TTS) system, by equipping a pre-trained diffusion-based TTS model with a personalized adapter. VoiceTailor identifies pivotal modules that benefit from the adapter based on a weight change ratio analysis. We utilize Low-Rank Adaptation (LoRA) as a parameter-efficient adaptation method and incorporate the adapter into pivotal modules of the pre-trained diffusion decoder. To achieve powerful adaptation performance with few parameters, we explore various guidance techniques for speaker adaptation and investigate the best strategies to strengthen speaker information. VoiceTailor demonstrates comparable speaker adaptation performance to existing adaptive TTS models by fine-tuning only 0.25\% of the total parameters. VoiceTailor shows strong robustness when adapting to a wide range of real-world speakers, as shown in the demo.
format Preprint
id arxiv_https___arxiv_org_abs_2408_14739
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle VoiceTailor: Lightweight Plug-In Adapter for Diffusion-Based Personalized Text-to-Speech
Kim, Heeseung
Lee, Sang-gil
Yeom, Jiheum
Lee, Che Hyun
Kim, Sungwon
Yoon, Sungroh
Sound
Audio and Speech Processing
We propose VoiceTailor, a parameter-efficient speaker-adaptive text-to-speech (TTS) system, by equipping a pre-trained diffusion-based TTS model with a personalized adapter. VoiceTailor identifies pivotal modules that benefit from the adapter based on a weight change ratio analysis. We utilize Low-Rank Adaptation (LoRA) as a parameter-efficient adaptation method and incorporate the adapter into pivotal modules of the pre-trained diffusion decoder. To achieve powerful adaptation performance with few parameters, we explore various guidance techniques for speaker adaptation and investigate the best strategies to strengthen speaker information. VoiceTailor demonstrates comparable speaker adaptation performance to existing adaptive TTS models by fine-tuning only 0.25\% of the total parameters. VoiceTailor shows strong robustness when adapting to a wide range of real-world speakers, as shown in the demo.
title VoiceTailor: Lightweight Plug-In Adapter for Diffusion-Based Personalized Text-to-Speech
topic Sound
Audio and Speech Processing
url https://arxiv.org/abs/2408.14739