최소 단어 이상 선택하여야 합니다.
최대 10 단어까지만 선택 가능합니다.
다음과 같은 기능을 한번의 로그인으로 사용 할 수 있습니다.
NTIS 바로가기IEEE/ACM transactions on audio, speech, and language processing, v.30, 2022년, pp.1558 - 1571
Huang, Sung-Feng (Graduate Institute of Communication Engineering, National Taiwan University, Taipei, Taiwan) , Lin, Chyi-Jiunn (Department of Electrical Engineering, National Taiwan University, Taipei, Taiwan) , Liu, Da-Rong (Graduate Institute of Communication Engineering, National Taiwan University, Taipei, Taiwan) , Chen, Yi-Chen (Graduate Institute of Communication Engineering, National Taiwan University, Taipei, Taiwan) , Lee, Hung-yi (Department of Electrical Engineering, National Taiwan University, Taipei, Taiwan)
초록이 없습니다.
WaveNet: A generative model for raw audio Oord
Proc. Int. Conf. Learn. Representations FastSpeech 2: Fast and high-quality end-to-end text-to-speech Ren 2021
Proc. Adv. Neural Inf. Process. Syst. Deep voice 2: Multi-speaker neural text-to-speech Gibiansky 30 2966 2017
Proc. Int. Conf. Learn. Representations Deep voice 3: 2000-speaker neural text-to-speech Ping 214 2018
Proc. 32nd Int. Conf. Neural Inf. Process. Syst. Transfer learning from speaker verification to multispeaker text-to-speech synthesis Jia 4485 2018
Proc. 32nd Int. Conf. Neural Inf. Process. Syst. Neural voice cloning with a few samples Arik 10040 2018
Proc. Int. Conf. Learn. Representations Sample efficient adaptive text-to-speech Chen 2019
Proc. Int. Conf. Learn. Representations AdaSpeech: Adaptive text to speech for custom voice Chen 2021
Proc. Int. Conf. Learn. Representations VoiceLoop: Voice fitting and synthesis via a phonological loop Taigman 2018
Proc. Int. Conf. Mach. Learn. Model-agnostic meta-learning for fast adaptation of deep networks Finn 1126 2017
Revisiting meta-learning as supervised learning Chao 2020
Proc. Int. Conf. Learn. Representations Rapid learning or feature reuse? Towards understanding the effectiveness of MAML Raghu 2020
Adv. Neural Inf. Process. Syst. Wav2Vec 2.0: A framework for self-supervised learning of speech representations Baevski 33 12449 2020
Liu, Andy T., Li, Shang-Wen, Lee, Hung-yi. TERA: Self-Supervised Learning of Transformer Encoder Representation for Speech. IEEE/ACM transactions on audio, speech, and language processing, vol.29, 2351-2366.
Representation learning with contrastive predictive coding Oord 2018
version 0.92), [Sound CSTR VCTK Corpus: English multi-speaker corpus for CSTR voice cloning toolkit Yamagishi 2019
Adv. Neural Inf. Process. Syst. MelGAN: Generative adversarial networks for conditional waveform synthesis Kumar 32 2019
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