Any-to-Any Voice Conversion with F0 and Timbre Disentanglement and Novel Timbre Conditioning

Author:

Kovela Sudheer1,Valle Rafael1,Dantrey Ambrish1,Catanzaro Bryan1

Affiliation:

1. NVIDIA

Publisher

IEEE

Reference20 articles.

1. Instance normalization: The missing ingredient for fast stylization;ulyanov,2016

2. Conformer: Convolution-augmented Transformer for Speech Recognition

3. UnivNet: A Neural Vocoder with Multi-Resolution Spectrogram Discriminators for High-Fidelity Waveform Generation

4. WORLD: A Vocoder-Based High-Quality Speech Synthesis System for Real-Time Applications

5. Visualizing data using t-sne;van der maaten;Journal of Machine Learning Research,2008

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1. Speaker Anonymization: Disentangling Speaker Features from Pre-Trained Speech Embeddings for Voice Conversion;Applied Sciences;2024-04-30

2. High-Fidelity Neural Phonetic Posteriorgrams;2024 IEEE International Conference on Acoustics, Speech, and Signal Processing Workshops (ICASSPW);2024-04-14

3. STREAMVC: Real-Time Low-Latency Voice Conversion;ICASSP 2024 - 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP);2024-04-14

4. A measure of differences in speech signals by the voice timbre;Measurement Techniques;2024-01

5. Fast Neural Speech Waveform Generative Models With Fully-Connected Layer-Based Upsampling;IEEE Access;2024

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