VoiceGuider: Enhancing Out-of-Domain Performance in Parameter-Efficient Speaker-Adaptive Text-to-Speech via Autoguidance
<|reference_start|>VoiceGuider: Enhancing Out-of-Domain Performance in Parameter-Efficient Speaker-Adaptive Text-to-Speech via Autoguidance: When applying parameter-efficient finetuning via LoRA onto speaker adaptive text-to-speech models, adaptation performance may decline compared to full-finetuned counterparts, especially for out-of-domain speakers. Here, we propose VoiceGuider, a parameter-efficient speaker adaptive text-to-speech system reinforced with autoguidance to enhance the speaker adaptation performance, reducing the gap against full-finetuned models. We carefully explore various ways of strengthening autoguidance, ultimately finding the optimal strategy. VoiceGuider as a result shows robust adaptation performance especially on extreme out-of-domain speech data. We provide audible samples in our demo page.<|reference_end|>
@article{yeom2024voiceguider:,
    title={VoiceGuider: Enhancing Out-of-Domain Performance in Parameter-Efficient
  Speaker-Adaptive Text-to-Speech via Autoguidance},
    author={Jiheum Yeom, Heeseung Kim, Jooyoung Choi, Che Hyun Lee, Nohil Park,
  Sungroh Yoon},
    journal={arXiv preprint arXiv:2409.15759},
    year={2024},
    archivePrefix={arXiv},
    eprint={2409.15759},
    primaryClass={cs.SD eess.AS}
}