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

Autor:	Kim, Heeseung, Lee, Sang-gil, Yeom, Jiheum, Lee, Che Hyun, Kim, Sungwon, Yoon, Sungroh
Rok vydání:	2024
Předmět:	Computer Science - Sound Electrical Engineering and Systems Science - Audio and Speech Processing
Druh dokumentu:	Working Paper
Popis:	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. Comment: INTERSPEECH 2024
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2408.14739 Zobrazit plný text záznamu View this record from Arxiv