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FlowVocoder: A small Footprint Neural Vocoder based Normalizing flow for Speech Synthesis

arXiv 2109.13675 ↗First posted 27 Sep 2021cs.SD cs.LG eess.AScited by 0

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Abstract (arXiv)

Recently, autoregressive neural vocoders have provided remarkable performance in generating high-fidelity speech and have been able to produce synthetic speech in real-time. However, autoregressive neural vocoders such as WaveFlow are capable of modeling waveform signals from mel-spectrogram, its number of parameters is significant to deploy on edge devices. Though NanoFlow, which has a small number of parameters, is a state-of-the-art autoregressive neural vocoder, the performance of NanoFlow is marginally lower than WaveFlow. Therefore, we propose a new type of autoregressive neural vocoder called FlowVocoder, which has a small memory footprint and is capable of generating high-fidelity audio in real-time. Our proposed model improves the density estimation of flow blocks by utilizing a mixture of Cumulative Distribution Functions (CDF) for bipartite transformation. Hence, the proposed model is capable of modeling waveform signals, while its memory footprint is much smaller than WaveFlow. As shown in experiments, FlowVocoder achieves competitive results with baseline methods in terms of both subjective and objective evaluation, also, it is more suitable for real-time text-to-speech applications.

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References · 18

  1. 2016WaveNet: A Generative Model for Raw Audiocited by 1,710
  2. 2020HiFi-GAN: Generative Adversarial Networks for Efficient and High Fidelity Speech Synthesiscited by 1,139
  3. 2017Natural TTS Synthesis by Conditioning WaveNet on Mel Spectrogram Predictionscited by 800
  4. 2019MelGAN: Generative Adversarial Networks for Conditional Waveform Synthesiscited by 351
  5. 2019Parallel WaveGAN: A fast waveform generation model based on generative adversarial networks with multi-resolution spectrogramcited by 337
  6. 2018WaveGlow: A Flow-based Generative Network for Speech Synthesiscited by 308
  7. 2019Flow++: Improving Flow-Based Generative Models with Variational Dequantization and Architecture Designcited by 258
  8. 2018Adversarial Audio Synthesiscited by 222
  9. 2017Parallel WaveNet: Fast High-Fidelity Speech Synthesiscited by 214
  10. 2019High Fidelity Speech Synthesis with Adversarial Networkscited by 90
  11. 2021UnivNet: A Neural Vocoder with Multi-Resolution Spectrogram Discriminators for High-Fidelity Waveform Generationcited by 71
  12. 2018ClariNet: Parallel Wave Generation in End-to-End Text-to-Speechcited by 70
6 more
  1. 2020Multi-band MelGAN: Faster Waveform Generation for High-Quality Text-to-Speechcited by 63
  2. 2018FloWaveNet : A Generative Flow for Raw Audiocited by 54
  3. 2019WaveFlow: A Compact Flow-based Model for Raw Audiocited by 51
  4. 2020StyleMelGAN: An Efficient High-Fidelity Adversarial Vocoder with Temporal Adaptive Normalizationcited by 26
  5. 2019Probability density distillation with generative adversarial networks for high-quality parallel waveform generationcited by 14
  6. 2020NanoFlow: Scalable Normalizing Flows with Sublinear Parameter Complexitycited by 9

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