Kan-bayashi LJSpeech Open-Source Text-to-Speech Model - Free Deployment for Natural Voice Synthesis

Kan Bayashi Ljspeech Joint Finetune Conformer Fastspeech2 Hifigan

Developed by espnet

This is a text-to-speech (TTS) model based on ESPnet2, trained using the LJSpeech dataset, combining Conformer, FastSpeech2, and HiFi-GAN architectures.

Speech Synthesis English#Joint Fine-tuning TTS #Conformer Architecture #HiFi-GAN Vocoder

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Release Time : 3/2/2022

Model Overview

This model is a high-quality English text-to-speech system capable of converting text input into natural and fluent speech output.

Model Features

Joint Architecture

Combines the sequence modeling capability of Conformer, the efficient synthesis of FastSpeech2, and the high-quality vocoder of HiFi-GAN.

High-Quality Speech

Capable of generating natural and fluent English speech.

ESPnet2 Integration

Based on the ESPnet2 framework, facilitating integration with other speech processing tools.

Model Capabilities

Text-to-Speech

English Speech Synthesis

Use Cases

Speech Synthesis Applications

Audiobook Generation

Convert e-book text into natural speech

Generate high-quality English audiobooks

Voice Assistants

Provide natural speech output for smart devices

Enhance the naturalness of user experience

🚀 ESPnet2 TTS Pretrained Model

This is a pre - trained TTS model in ESPnet2, which can be used for text - to - speech tasks. It provides a practical solution for audio processing.

🚀 Quick Start

Import Information

♻️ Imported from https://zenodo.org/record/5498896/

This model was trained by kan - bayashi using ljspeech/tts1 recipe in espnet.

Demo: How to use in ESPnet2

# coming soon

📄 License

This model is under the CC - BY - 4.0 license.

📚 Documentation

Citing ESPnet

@inproceedings{watanabe2018espnet,
  author={Shinji Watanabe and Takaaki Hori and Shigeki Karita and Tomoki Hayashi and Jiro Nishitoba and Yuya Unno and Nelson {Enrique Yalta Soplin} and Jahn Heymann and Matthew Wiesner and Nanxin Chen and Adithya Renduchintala and Tsubasa Ochiai},
  title={{ESPnet}: End-to-End Speech Processing Toolkit},
  year={2018},
  booktitle={Proceedings of Interspeech},
  pages={2207--2211},
  doi={10.21437/Interspeech.2018-1456},
  url={http://dx.doi.org/10.21437/Interspeech.2018-1456}
}
@inproceedings{hayashi2020espnet,
  title={{Espnet-TTS}: Unified, reproducible, and integratable open source end-to-end text-to-speech toolkit},
  author={Hayashi, Tomoki and Yamamoto, Ryuichi and Inoue, Katsuki and Yoshimura, Takenori and Watanabe, Shinji and Toda, Tomoki and Takeda, Kazuya and Zhang, Yu and Tan, Xu},
  booktitle={Proceedings of IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)},
  pages={7654--7658},
  year={2020},
  organization={IEEE}
}

or arXiv:

@misc{watanabe2018espnet,
      title={ESPnet: End-to-End Speech Processing Toolkit}, 
      author={Shinji Watanabe and Takaaki Hori and Shigeki Karita and Tomoki Hayashi and Jiro Nishitoba and Yuya Unno and Nelson Enrique Yalta Soplin and Jahn Heymann and Matthew Wiesner and Nanxin Chen and Adithya Renduchintala and Tsubasa Ochiai},
      year={2018},
      eprint={1804.00015},
      archivePrefix={arXiv},
      primaryClass={cs.CL}
}

Property	Details
Tags	espnet, audio, text - to - speech
Datasets	ljspeech
Model Name	kan - bayashi/ljspeech_joint_finetune_conformer_fastspeech2_hifigan

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