40 citations · 51 across the 5 of their papers we have counts for
5 papers
ResGrad: Residual Denoising Diffusion Probabilistic Models for Text to Speech
Zehua Chen, Yihan Wu, Yichong Leng +9
Denoising Diffusion Probabilistic Models (DDPMs) are emerging in text-to-speech (TTS) synthesis because of their strong capability of generating high-fidelity samples. However, the…
On how to avoid exacerbating spurious correlations when models are overparameterized
Tina Behnia, Ke Wang, Christos Thrampoulidis
Overparameterized models fail to generalize well in the presence of data imbalance even when combined with traditional techniques for mitigating imbalances. This paper focuses on i…
InferGrad: Improving Diffusion Models for Vocoder by Considering Inference in Training
Zehua Chen, Xu Tan, Ke Wang +4
Denoising diffusion probabilistic models (diffusion models for short) require a large number of iterations in inference to achieve the generation quality that matches or surpasses…
Empirical Evaluation of Speaker Adaptation on DNN based Acoustic Model
Ke Wang, Junbo Zhang, Yujun Wang +1
Speaker adaptation aims to estimate a speaker specific acoustic model from a speaker independent one to minimize the mismatch between the training and testing conditions arisen fro…
Investigating Generative Adversarial Networks based Speech Dereverberation for Robust Speech Recognition
Ke Wang, Junbo Zhang, Sining Sun +3
We investigate the use of generative adversarial networks (GANs) in speech dereverberation for robust speech recognition. GANs have been recently studied for speech enhancement to…