@ -141,12 +141,11 @@ Via the easy-to-use, efficient, flexible and scalable implementation, our vision
- 🤗 2021.12.14: Our PaddleSpeech [ASR](https://huggingface.co/spaces/KPatrick/PaddleSpeechASR) and [TTS](https://huggingface.co/spaces/akhaliq/paddlespeech) Demos on Hugging Face Spaces are available!
- 👏🏻 2021.12.10: PaddleSpeech CLI is available for Audio Classification, Automatic Speech Recognition, Speech Translation (English to Chinese) and Text-to-Speech.
### Communication
If you are in China, we recommend you to join our WeChat group to contact directly with our team members!
### Community
- Scan the QR code below with your Wechat, you can access to official technical exchange group. Look forward to your participation.
Up to now, **Linux** supports CLI for the all our tasks, **Mac OSX and Windows** only supports PaddleSpeech CLI for Audio Classification, Speech-to-Text and Text-to-Speech. Please see [installation](./docs/source/install.md) for other alternatives.
<aname="quickstart"></a>
## Quick Start
Developers can have a try of our models with [PaddleSpeech Command Line](./demos/README.md). Change `--input` to test your own audio/text.
@ -177,7 +177,7 @@ paddlespeech st --input input_16k.wav
- web demo for Text to Speech is integrated to [Huggingface Spaces](https://huggingface.co/spaces) with [Gradio](https://github.com/gradio-app/gradio). See Demo: [TTS Demo](https://huggingface.co/spaces/akhaliq/paddlespeech)
@ -388,6 +388,8 @@ The current hyperlinks redirect to [Previous Parakeet](https://github.com/Paddle
Normally, [Speech SoTA](https://paperswithcode.com/area/speech), [Audio SoTA](https://paperswithcode.com/area/audio) and [Music SoTA](https://paperswithcode.com/area/music) give you an overview of the hot academic topics in the related area. To focus on the tasks in PaddleSpeech, you will find the following guidelines are helpful to grasp the core ideas.
The Text-to-Speech module is originally called [Parakeet](https://github.com/PaddlePaddle/Parakeet), and now merged with this repository. If you are interested in academic research about this task, please see [TTS research overview](https://github.com/PaddlePaddle/PaddleSpeech/tree/develop/docs/source/tts#overview). Also, [this document](https://github.com/PaddlePaddle/PaddleSpeech/blob/develop/docs/source/tts/models_introduction.md) is a good guideline for the pipeline components.
You are warmly welcome to submit questions in [discussions](https://github.com/PaddlePaddle/PaddleSpeech/discussions) and bug reports in [issues](https://github.com/PaddlePaddle/PaddleSpeech/issues)! Also, we highly appreciate if you are willing to contribute to this project!