2 papers
eess.AS2020
An empirical study of Conv-TasNet
Berkan Kadioglu, Michael Horgan, Xiaoyu Liu +3
Conv-TasNet is a recently proposed waveform-based deep neural network that achieves state-of-the-art performance in speech source separation. Its architecture consists of a learnab…
cs.SD2018
Voice Conversion with Conditional SampleRNN
Cong Zhou, Michael Horgan, Vivek Kumar +2
Here we present a novel approach to conditioning the SampleRNN generative model for voice conversion (VC). Conventional methods for VC modify the perceived speaker identity by conv…