29 citations · 91 across the 19 of their papers we have counts for
5 papers · 1 filter
Direct Noisy Speech Modeling for Noisy-to-Noisy Voice Conversion
Chao Xie, Yi-Chiao Wu, Patrick Lumban Tobing +2
Beyond the conventional voice conversion (VC) where the speaker information is converted without altering the linguistic content, the background sounds are informative and need to…
Noisy-to-Noisy Voice Conversion Framework with Denoising Model
Chao Xie, Yi-Chiao Wu, Patrick Lumban Tobing +2
In a conventional voice conversion (VC) framework, a VC model is often trained with a clean dataset consisting of speech data carefully recorded and selected by minimizing backgrou…
Low-Latency Real-Time Non-Parallel Voice Conversion based on Cyclic Variational Autoencoder and Multiband WaveRNN with Data-Driven Linear Prediction
Patrick Lumban Tobing, Tomoki Toda
This paper presents a low-latency real-time (LLRT) non-parallel voice conversion (VC) framework based on cyclic variational autoencoder (CycleVAE) and multiband WaveRNN with data-d…
High-Fidelity and Low-Latency Universal Neural Vocoder based on Multiband WaveRNN with Data-Driven Linear Prediction for Discrete Waveform Modeling
Patrick Lumban Tobing, Tomoki Toda
This paper presents a novel high-fidelity and low-latency universal neural vocoder framework based on multiband WaveRNN with data-driven linear prediction for discrete waveform mod…
crank: An Open-Source Software for Nonparallel Voice Conversion Based on Vector-Quantized Variational Autoencoder
Kazuhiro Kobayashi, Wen-Chin Huang, Yi-Chiao Wu +3
In this paper, we present an open-source software for developing a nonparallel voice conversion (VC) system named crank. Although we have released an open-source VC software based…