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Generative Adversarial Training for Text-to-Speech Synthesis Based on Raw Phonetic Input and Explicit Prosody Modelling

arXiv 2310.09636 ↗First posted 14 Oct 2023cs.LGcited by 0

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Abstract (arXiv)

We describe an end-to-end speech synthesis system that uses generative adversarial training. We train our Vocoder for raw phoneme-to-audio conversion, using explicit phonetic, pitch and duration modeling. We experiment with several pre-trained models for contextualized and decontextualized word embeddings and we introduce a new method for highly expressive character voice matching, based on discreet style tokens.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 17 of its 27 references that are in the map. First posted on arXiv 14 Oct 2023.

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References · 17

  1. 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,399
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  4. 2016WaveNet: A Generative Model for Raw Audiocited by 1,722
  5. 2016Enriching Word Vectors with Subword Informationcited by 1,583
  6. 2020HiFi-GAN: Generative Adversarial Networks for Efficient and High Fidelity Speech Synthesiscited by 1,154
  7. 2017Tacotron: Towards End-to-End Speech Synthesiscited by 490
  8. 2019CamemBERT: a Tasty French Language Modelcited by 368
  9. 2019MelGAN: Generative Adversarial Networks for Conditional Waveform Synthesiscited by 354
  10. 2018Efficient Neural Audio Synthesiscited by 219
  11. 2017Parallel WaveNet: Fast High-Fidelity Speech Synthesiscited by 215
  12. 2016SampleRNN: An Unconditional End-to-End Neural Audio Generation Modelcited by 110
5 more
  1. 2021Hi-Fi Multi-Speaker English TTS Datasetcited by 60
  2. 2018FloWaveNet : A Generative Flow for Raw Audiocited by 54
  3. 2022JETS: Jointly Training FastSpeech2 and HiFi-GAN for End to End Text to Speechcited by 26
  4. 2022DelightfulTTS 2: End-to-End Speech Synthesis with Adversarial Vector-Quantized Auto-Encoderscited by 15
  5. 2016Fast Wavenet Generation Algorithmcited by 14

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