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pro vyhledávání: '"Lee, Sang‐gil"'
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 o
Externí odkaz:
http://arxiv.org/abs/2408.14739
Autor:
Kong, Zhifeng, Lee, Sang-gil, Ghosal, Deepanway, Majumder, Navonil, Mehrish, Ambuj, Valle, Rafael, Poria, Soujanya, Catanzaro, Bryan
It is an open challenge to obtain high quality training data, especially captions, for text-to-audio models. Although prior methods have leveraged \textit{text-only language models} to augment and improve captions, such methods have limitations relat
Externí odkaz:
http://arxiv.org/abs/2406.15487
Despite the fact that text-to-video (TTV) model has recently achieved remarkable success, there have been few approaches on TTV for its extension to video editing. Motivated by approaches on TTV models adapting from diffusion-based text-to-image (TTI
Externí odkaz:
http://arxiv.org/abs/2303.07945
Despite recent progress in generative adversarial network (GAN)-based vocoders, where the model generates raw waveform conditioned on acoustic features, it is challenging to synthesize high-fidelity audio for numerous speakers across various recordin
Externí odkaz:
http://arxiv.org/abs/2206.04658
Autor:
Yu, Su-Jeong, So, Yun-Sang, Lim, Changjin, Cho, Chi Heung, Lee, Sang-Gil, Yoo, Sang-Ho, Park, Cheon-Seok, Lee, Byung-Hoo, Min, Kyung Hyun, Seo, Dong-Ho
Publikováno v:
In Food Chemistry 1 August 2024 448
The computer-aided diagnosis of focal liver lesions (FLLs) can help improve workflow and enable correct diagnoses; FLL detection is the first step in such a computer-aided diagnosis. Despite the recent success of deep-learning-based approaches in det
Externí odkaz:
http://arxiv.org/abs/2112.01535
Autor:
Lee, Hye-Rin, Kim, Ye-Jin, Lee, Chang-Young, Lee, Sang Gil, Nam, Tae Gyu, Park, Cheon-Seok, Seo, Dong-Ho
Publikováno v:
In Food Bioscience June 2024 59
Autor:
Lee, Sang-gil, Kim, Heeseung, Shin, Chaehun, Tan, Xu, Liu, Chang, Meng, Qi, Qin, Tao, Chen, Wei, Yoon, Sungroh, Liu, Tie-Yan
Denoising diffusion probabilistic models have been recently proposed to generate high-quality samples by estimating the gradient of the data density. The framework defines the prior noise as a standard Gaussian distribution, whereas the corresponding
Externí odkaz:
http://arxiv.org/abs/2106.06406
Normalizing flows (NFs) have become a prominent method for deep generative models that allow for an analytic probability density estimation and efficient synthesis. However, a flow-based network is considered to be inefficient in parameter complexity
Externí odkaz:
http://arxiv.org/abs/2006.06280
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