e2 tts pytorch下載 - e2 tts pytorch原始碼下載

E2 TTS - Pytorch

在 Pytorch 中實現 E2-TTS，極其簡單的完全非自回歸零樣本 TTS

此儲存庫與論文的不同之處在於它使用多流轉換器來處理文字和音頻，並以 E2 方式對每個轉換器區塊進行調節。

它還包括經 Manmay 證明的即興創作，其中文字只是簡單地插入到音訊的長度中以進行調節。您可以透過在E2TTS上設定interpolated_text = True來嘗試此操作

欣賞

Manmay 貢獻了有效的端到端培訓程式碼！
Lucas Newman 貢獻了程式碼，提供了有用的回饋，並分享了第一組積極的實驗！
Jing 分享了多語言（英語+中文）資料集的第二個陽性結果！
科伊斯和曼梅報告了第三次和第四次成功運行。告別對準工程

安裝

$ pip install e2-tts-pytorch

用法

 import torch

from e2_tts_pytorch import (
    E2TTS ,
    DurationPredictor
)

duration_predictor = DurationPredictor (
    transformer = dict (
        dim = 512 ,
        depth = 8 ,
    )
)

mel = torch . randn ( 2 , 1024 , 100 )
text = [ 'Hello' , 'Goodbye' ]

loss = duration_predictor ( mel , text = text )
loss . backward ()

e2tts = E2TTS (
    duration_predictor = duration_predictor ,
    transformer = dict (
        dim = 512 ,
        depth = 8        
    ),
)

out = e2tts ( mel , text = text )
out . loss . backward ()

sampled = e2tts . sample ( mel [:, : 5 ], text = text )

引文

 @inproceedings { Eskimez2024E2TE ,
    title   = { E2 TTS: Embarrassingly Easy Fully Non-Autoregressive Zero-Shot TTS } ,
    author  = { Sefik Emre Eskimez and Xiaofei Wang and Manthan Thakker and Canrun Li and Chung-Hsien Tsai and Zhen Xiao and Hemin Yang and Zirun Zhu and Min Tang and Xu Tan and Yanqing Liu and Sheng Zhao and Naoyuki Kanda } ,
    year    = { 2024 } ,
    url     = { https://api.semanticscholar.org/CorpusID:270738197 }
}

 @inproceedings { Darcet2023VisionTN ,
    title   = { Vision Transformers Need Registers } ,
    author  = { Timoth'ee Darcet and Maxime Oquab and Julien Mairal and Piotr Bojanowski } ,
    year    = { 2023 } ,
    url     = { https://api.semanticscholar.org/CorpusID:263134283 }
}

 @article { Bao2022AllAW ,
    title   = { All are Worth Words: A ViT Backbone for Diffusion Models } ,
    author  = { Fan Bao and Shen Nie and Kaiwen Xue and Yue Cao and Chongxuan Li and Hang Su and Jun Zhu } ,
    journal = { 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) } ,
    year    = { 2022 } ,
    pages   = { 22669-22679 } ,
    url     = { https://api.semanticscholar.org/CorpusID:253581703 }
}

 @article { Burtsev2021MultiStreamT ,
    title     = { Multi-Stream Transformers } ,
    author    = { Mikhail S. Burtsev and Anna Rumshisky } ,
    journal   = { ArXiv } ,
    year      = { 2021 } ,
    volume    = { abs/2107.10342 } ,
    url       = { https://api.semanticscholar.org/CorpusID:236171087 }
}

 @inproceedings { Sadat2024EliminatingOA ,
    title   = { Eliminating Oversaturation and Artifacts of High Guidance Scales in Diffusion Models } ,
    author  = { Seyedmorteza Sadat and Otmar Hilliges and Romann M. Weber } ,
    year    = { 2024 } ,
    url     = { https://api.semanticscholar.org/CorpusID:273098845 }
}

 @article { Gulati2020ConformerCT ,
    title   = { Conformer: Convolution-augmented Transformer for Speech Recognition } ,
    author  = { Anmol Gulati and James Qin and Chung-Cheng Chiu and Niki Parmar and Yu Zhang and Jiahui Yu and Wei Han and Shibo Wang and Zhengdong Zhang and Yonghui Wu and Ruoming Pang } ,
    journal = { ArXiv } ,
    year    = { 2020 } ,
    volume  = { abs/2005.08100 } ,
    url     = { https://api.semanticscholar.org/CorpusID:218674528 }
}

 @article { Yang2024ConsistencyFM ,
    title   = { Consistency Flow Matching: Defining Straight Flows with Velocity Consistency } ,
    author  = { Ling Yang and Zixiang Zhang and Zhilong Zhang and Xingchao Liu and Minkai Xu and Wentao Zhang and Chenlin Meng and Stefano Ermon and Bin Cui } ,
    journal = { ArXiv } ,
    year    = { 2024 } ,
    volume  = { abs/2407.02398 } ,
    url     = { https://api.semanticscholar.org/CorpusID:270878436 }
}

 @article { Li2024SwitchEA ,
    title   = { Switch EMA: A Free Lunch for Better Flatness and Sharpness } ,
    author  = { Siyuan Li and Zicheng Liu and Juanxi Tian and Ge Wang and Zedong Wang and Weiyang Jin and Di Wu and Cheng Tan and Tao Lin and Yang Liu and Baigui Sun and Stan Z. Li } ,
    journal = { ArXiv } ,
    year    = { 2024 } ,
    volume  = { abs/2402.09240 } ,
    url     = { https://api.semanticscholar.org/CorpusID:267657558 }
}

 @inproceedings { Zhou2024ValueRL ,
    title   = { Value Residual Learning For Alleviating Attention Concentration In Transformers } ,
    author  = { Zhanchao Zhou and Tianyi Wu and Zhiyun Jiang and Zhenzhong Lan } ,
    year    = { 2024 } ,
    url     = { https://api.semanticscholar.org/CorpusID:273532030 }
}

 @inproceedings { Duvvuri2024LASERAW ,
    title   = { LASER: Attention with Exponential Transformation } ,
    author  = { Sai Surya Duvvuri and Inderjit S. Dhillon } ,
    year    = { 2024 } ,
    url     = { https://api.semanticscholar.org/CorpusID:273849947 }
}

 @article { Zhu2024HyperConnections ,
    title   = { Hyper-Connections } ,
    author  = { Defa Zhu and Hongzhi Huang and Zihao Huang and Yutao Zeng and Yunyao Mao and Banggu Wu and Qiyang Min and Xun Zhou } ,
    journal = { ArXiv } ,
    year    = { 2024 } ,
    volume  = { abs/2409.19606 } ,
    url     = { https://api.semanticscholar.org/CorpusID:272987528 }
}