[Paper 리뷰] One-Shot Voice Conversion by Separating Speaker and Content Representations with Instance Normalization
One-Shot Voice Conversion by Separating Speaker and Content Representations with Instance NormalizationSource, target speaker의 example utterance만으로 voice conversion을 수행할 수 있어야 함AdaIN-VCInstance Normalization을 도입해 speaker, content representation을 disentanlging 함Unseen speaker에 대해 one-shot voice conversion이 가능논문 (INTERSPEECH 2019) : Paper Link1. IntroductionVoice Conversion (VC)는 linguistic conten..
[Paper 리뷰] AGAIN-VC: A One-Shot Voice Conversion Using Activation Guidance and Adaptive Instance Normalization
AGAIN-VC: A One-Shot Voice Conversion Using Activation Guidance and Adaptive Instance NormalizationVoice Conversion은 일반적으로 disentangle-based learning을 사용하여 speaker와 linguistic content를 분리한 다음, speaker information을 target speaker로 변환하는 방식을 활용함AGAIN-VCActivation guidance와 Adaptive Instance Normalization을 도입해 speaker information의 유출을 방지Single encoder-decoder로 구성되어 합성 품질과 speaker similarity를 향상 논문 (..