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Anyone GAN Sing

arXiv 2102.11058 ↗First posted 22 Feb 2021cs.SD cs.LG eess.AScited by 0

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Abstract (arXiv)

The problem of audio synthesis has been increasingly solved using deep neural networks. With the introduction of Generative Adversarial Networks (GAN), another efficient and adjective path has opened up to solve this problem. In this paper, we present a method to synthesize the singing voice of a person using a Convolutional Long Short-term Memory (ConvLSTM) based GAN optimized using the Wasserstein loss function. Our work is inspired by WGANSing by Chandna et al. Our model inputs consecutive frame-wise linguistic and frequency features, along with singer identity and outputs vocoder features. We train the model on a dataset of 48 English songs sung and spoken by 12 non-professional singers. For inference, sequential blocks are concatenated using an overlap-add procedure. We test the model using the Mel-Cepstral Distance metric and a subjective listening test with 18 participants.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 15 of its 23 references that are in the map. First posted on arXiv 22 Feb 2021.

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15 of 23 references.

References · 15

  1. 2015U-Net: Convolutional Networks for Biomedical Image Segmentationcited by 19,713
  2. 2018A Style-Based Generator Architecture for Generative Adversarial Networkscited by 6,013
  3. 2016Image-to-Image Translation with Conditional Adversarial Networkscited by 4,527
  4. 2014Conditional Generative Adversarial Netscited by 2,162
  5. 2015Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networkscited by 2,054
  6. 2016WaveNet: A Generative Model for Raw Audiocited by 1,722
  7. 2015Convolutional LSTM Network: A Machine Learning Approach for Precipitation Nowcastingcited by 1,436
  8. 2016Generative Adversarial Text to Image Synthesiscited by 735
  9. 2016StackGAN: Text to Photo-realistic Image Synthesis with Stacked Generative Adversarial Networkscited by 577
  10. 2017SEGAN: Speech Enhancement Generative Adversarial Networkcited by 166
  11. 2017MidiNet: A Convolutional Generative Adversarial Network for Symbolic-domain Music Generationcited by 72
  12. 2019Adversarially Trained End-to-end Korean Singing Voice Synthesis Systemcited by 22
3 more
  1. 2017A Neural Parametric Singing Synthesizercited by 14
  2. 2019WGANSing: A Multi-Voice Singing Voice Synthesizer Based on the Wasserstein-GANcited by 13
  3. 2019Generative Moment Matching Network-based Random Modulation Post-filter for DNN-based Singing Voice Synthesis and Neural Double-trackingcited by 1

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