mlsanityData to 7 Oct 2026

Generating Diverse Vocal Bursts with StyleGAN2 and MEL-Spectrograms

arXiv 2206.12563 ↗First posted 25 Jun 2022cs.SD cs.LG eess.AScited by 3

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Abstract (arXiv)

We describe our approach for the generative emotional vocal burst task (ExVo Generate) of the ICML Expressive Vocalizations Competition. We train a conditional StyleGAN2 architecture on mel-spectrograms of preprocessed versions of the audio samples. The mel-spectrograms generated by the model are then inverted back to the audio domain. As a result, our generated samples substantially improve upon the baseline provided by the competition from a qualitative and quantitative perspective for all emotions. More precisely, even for our worst-performing emotion (awe), we obtain an FAD of 1.76 compared to the baseline of 4.81 (as a reference, the FAD between the train/validation sets for awe is 0.776).

Key facts. Cited by 3 papers in the map (data through 7 Oct 2026). Builds on 14 of its 19 references that are in the map. First posted on arXiv 25 Jun 2022.

Builds on

14 of 19 references.

References · 14

  1. 2015Rethinking the Inception Architecture for Computer Visioncited by 5,451
  2. 2019Analyzing and Improving the Image Quality of StyleGANcited by 3,580
  3. 2018Large Scale GAN Training for High Fidelity Natural Image Synthesiscited by 2,609
  4. 2020Training Generative Adversarial Networks with Limited Datacited by 1,184
  5. 2017Natural TTS Synthesis by Conditioning WaveNet on Mel Spectrogram Predictionscited by 800
  6. 2019MelGAN: Generative Adversarial Networks for Conditional Waveform Synthesiscited by 351
  7. 2018WaveGlow: A Flow-based Generative Network for Speech Synthesiscited by 308
  8. 2018Style Tokens: Unsupervised Style Modeling, Control and Transfer in End-to-End Speech Synthesiscited by 257
  9. 2021A Survey on Neural Speech Synthesiscited by 182
  10. 2018A Variational Inequality Perspective on Generative Adversarial Networkscited by 144
  11. 2021Regularizing Generative Adversarial Networks under Limited Datacited by 105
  12. 2021TorchAudio: Building Blocks for Audio and Speech Processingcited by 83
2 more
  1. 2022The ICML 2022 Expressive Vocalizations Workshop and Competition: Recognizing, Generating, and Personalizing Vocal Burstscited by 16
  2. 2021Generating Diverse Realistic Laughter for Interactive Artcited by 5

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Cited by year

Citing papers per year: 2022: 2; 2023: 1.

3 papers.

  1. 2022An Overview of Affective Speech Synthesis and Conversion in the Deep Learning Eracited by 32
  2. 2023Disentanglement in a GAN for Unconditional Speech Synthesiscited by 4
  3. 2022GAN You Hear Me? Reclaiming Unconditional Speech Synthesis from Diffusion Modelscited by 3