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Found 6 papers, 3 papers with code
A Comparative Study of Voice Conversion Models with Large-Scale Speech and Singing Data: The T13 Systems for the Singing Voice Conversion Challenge 2023
This paper presents our systems (denoted as T13) for the singing voice conversion challenge (SVCC) 2023.
NNSVS: A Neural Network-Based Singing Voice Synthesis Toolkit
This paper describes the design of NNSVS, an open-source software for neural network-based singing voice synthesis research.
Nonparallel High-Quality Audio Super Resolution with Domain Adaptation and Resampling CycleGANs
Neural audio super-resolution models are typically trained on low- and high-resolution audio signal pairs.
Source-Filter HiFi-GAN: Fast and Pitch Controllable High-Fidelity Neural Vocoder
Our previous work, the unified source-filter GAN (uSFGAN) vocoder, introduced a novel architecture based on the source-filter theory into the parallel waveform generative adversarial network to achieve high voice quality and pitch controllability.
Unified Source-Filter GAN with Harmonic-plus-Noise Source Excitation Generation
To improve the source excitation modeling and generated sound quality, a new source excitation generation network separately generating periodic and aperiodic components is proposed.
Unified Source-Filter GAN: Unified Source-filter Network Based On Factorization of Quasi-Periodic Parallel WaveGAN
We propose a unified approach to data-driven source-filter modeling using a single neural network for developing a neural vocoder capable of generating high-quality synthetic speech waveforms while retaining flexibility of the source-filter model to control their voice characteristics.
