# TTS Papers
## Text Frontend
### Polyphone
- [【g2pM】g2pM: A Neural Grapheme-to-Phoneme Conversion Package for Mandarin Chinese Based on a New Open Benchmark Dataset](https://arxiv.org/abs/2004.03136)
- [Disambiguation of Chinese Polyphones in an End-to-End Framework with Semantic Features Extracted by Pre-trained BERT](https://www1.se.cuhk.edu.hk/~hccl/publications/pub/201909_INTERSPEECH_DongyangDAI.pdf)
- [Polyphone Disambiguation in Mandarin Chinese with Semi-Supervised Learning](https://www.isca-speech.org/archive/pdfs/interspeech_2021/shi21d_interspeech.pdf)
  * github: https://github.com/PaperMechanica/SemiPPL
- [WikipediaHomographData](https://github.com/google-research-datasets/WikipediaHomographData)
### Text Normalization
#### English
- [applenob/text_normalization](https://github.com/applenob/text_normalization)
### G2P
#### English
- [cmusphinx/g2p-seq2seq](https://github.com/cmusphinx/g2p-seq2seq)

## Acoustic Models
- [【AdaSpeech3】AdaSpeech 3: Adaptive Text to Speech for Spontaneous Style](https://arxiv.org/abs/2107.02530)
- [【AdaSpeech2】AdaSpeech 2: Adaptive Text to Speech with Untranscribed Data](https://arxiv.org/abs/2104.09715)
- [【AdaSpeech】AdaSpeech: Adaptive Text to Speech for Custom Voice](https://arxiv.org/abs/2103.00993)
- [【FastSpeech2】FastSpeech 2: Fast and High-Quality End-to-End Text to Speech](https://arxiv.org/abs/2006.04558)
- [【FastPitch】FastPitch: Parallel Text-to-speech with Pitch Prediction](https://arxiv.org/abs/2006.06873)
- [【SpeedySpeech】SpeedySpeech: Efficient Neural Speech Synthesis](https://arxiv.org/abs/2008.03802)
- [【FastSpeech】FastSpeech: Fast, Robust and Controllable Text to Speech](https://arxiv.org/abs/1905.09263)
- [【Transformer TTS】Neural Speech Synthesis with Transformer Network](https://arxiv.org/abs/1809.08895)
- [【Tacotron2】Natural TTS Synthesis by Conditioning WaveNet on Mel Spectrogram Predictions](https://arxiv.org/abs/1712.05884)

## Vocoders
- [【RefineGAN】RefineGAN: Universally Generating Waveform Better than Ground Truth with Highly Accurate Pitch and Intensity Responses](https://arxiv.org/abs/2111.00962)
- [【Fre-GAN】Fre-GAN: Adversarial Frequency-consistent Audio Synthesis](https://arxiv.org/abs/2106.02297)
- [【StyleMelGAN】StyleMelGAN: An Efficient High-Fidelity Adversarial Vocoder with Temporal Adaptive Normalization](https://arxiv.org/abs/2011.01557)
- [【Multi-band MelGAN】Multi-band MelGAN: Faster Waveform Generation for High-Quality Text-to-Speech](https://arxiv.org/abs/2005.05106)
- [【HiFi-GAN】HiFi-GAN: Generative Adversarial Networks for Efficient and High Fidelity Speech Synthesis](https://arxiv.org/abs/2010.05646)
- [【VocGAN】VocGAN: A High-Fidelity Real-time Vocoder with a Hierarchically-nested Adversarial Network](https://arxiv.org/abs/2007.15256)
- [【Parallel WaveGAN】Parallel WaveGAN: A fast waveform generation model based on generative adversarial networks with multi-resolution spectrogram](https://arxiv.org/abs/1910.11480)
- [【MelGAN】MelGAN: Generative Adversarial Networks for Conditional Waveform Synthesis](https://arxiv.org/abs/1910.06711)
- [【WaveFlow】WaveFlow: A Compact Flow-based Model for Raw Audio](https://arxiv.org/abs/1912.01219)
- [【LPCNet】LPCNet: Improving Neural Speech Synthesis Through Linear Prediction](https://arxiv.org/abs/1810.11846)
- [【WaveRNN】Efficient Neural Audio Synthesis](https://arxiv.org/abs/1802.08435)
## GAN TTS

- [【GAN TTS】High Fidelity Speech Synthesis with Adversarial Networks](https://arxiv.org/abs/1909.11646)

## Voice Cloning
- [【SV2TTS】Transfer Learning from Speaker Verification to Multispeaker Text-to-Speech Synthesis](https://arxiv.org/abs/1806.04558)
- [【GE2E】Generalized End-to-End Loss for Speaker Verification](https://arxiv.org/abs/1710.10467)
