未验证 提交 15b25199 编写于 作者: H Hui Zhang 提交者: GitHub

Merge pull request #1864 from zh794390558/doc

[doc] update readme with new feature
......@@ -151,14 +151,24 @@ For more synthesized audios, please refer to [PaddleSpeech Text-to-Speech sample
### Features
Via the easy-to-use, efficient, flexible and scalable implementation, our vision is to empower both industrial application and academic research, including training, inference & testing modules, and deployment process. To be more specific, this toolkit features at:
- 📦 **Ease of Use**: low barriers to install, and [CLI](#quick-start) is available to quick-start your journey.
- 📦 **Ease of Use**: low barriers to install, [CLI](#quick-start), [Server](#quick-start-server), and [Streaming Server](#quick-start-streaming-server) is available to quick-start your journey.
- 🏆 **Align to the State-of-the-Art**: we provide high-speed and ultra-lightweight models, and also cutting-edge technology.
- 🏆 **Streaming ASR and TTS System**: we provide production ready streaming asr and streaming tts system.
- 💯 **Rule-based Chinese frontend**: our frontend contains Text Normalization and Grapheme-to-Phoneme (G2P, including Polyphone and Tone Sandhi). Moreover, we use self-defined linguistic rules to adapt Chinese context.
- **Varieties of Functions that Vitalize both Industrial and Academia**:
- 🛎️ *Implementation of critical audio tasks*: this toolkit contains audio functions like Audio Classification, Speech Translation, Automatic Speech Recognition, Text-to-Speech Synthesis, etc.
- 📦 **Varieties of Functions that Vitalize both Industrial and Academia**:
- 🛎️ *Implementation of critical audio tasks*: this toolkit contains audio functions like Automatic Speech Recognition, Text-to-Speech Synthesis, Speaker Verfication, KeyWord Spotting, Audio Classification, and Speech Translation, etc.
- 🔬 *Integration of mainstream models and datasets*: the toolkit implements modules that participate in the whole pipeline of the speech tasks, and uses mainstream datasets like LibriSpeech, LJSpeech, AIShell, CSMSC, etc. See also [model list](#model-list) for more details.
- 🧩 *Cascaded models application*: as an extension of the typical traditional audio tasks, we combine the workflows of the aforementioned tasks with other fields like Natural language processing (NLP) and Computer Vision (CV).
### Recent Update
- 👏🏻 2022.05.06: `Streaming ASR` with `Punctuation Restoration` and `Token Timestamp`.
- 👏🏻 2022.05.06: `Server` is available for `Speaker Verification`, and `Punctuation Restoration`.
- 👏🏻 2022.04.28: `Streaming Server` is available for `Automatic Speech Recognition` and `Text-to-Speech`.
- 👏🏻 2022.03.28: `Server` is available for `Audio Classification`, `Automatic Speech Recognition` and `Text-to-Speech`.
- 👏🏻 2022.03.28: `CLI` is available for `Speaker Verification`.
- 🤗 2021.12.14: [ASR](https://huggingface.co/spaces/KPatrick/PaddleSpeechASR) and [TTS](https://huggingface.co/spaces/KPatrick/PaddleSpeechTTS) Demos on Hugging Face Spaces are available!
- 👏🏻 2021.12.10: `CLI` is available for `Audio Classification`, `Automatic Speech Recognition`, `Speech Translation (English to Chinese)` and `Text-to-Speech`.
### 🔥 Hot Activities
<!---
......@@ -171,15 +181,6 @@ Via the easy-to-use, efficient, flexible and scalable implementation, our vision
**Courses videos and related materials: https://aistudio.baidu.com/aistudio/education/group/info/25130**
### Recent Update
- 👏🏻 2022.04.28: PaddleSpeech Streaming Server is available for Automatic Speech Recognition and Text-to-Speech.
- 👏🏻 2022.03.28: PaddleSpeech Server is available for Audio Classification, Automatic Speech Recognition and Text-to-Speech.
- 👏🏻 2022.03.28: PaddleSpeech CLI is available for Speaker Verification.
- 🤗 2021.12.14: Our PaddleSpeech [ASR](https://huggingface.co/spaces/KPatrick/PaddleSpeechASR) and [TTS](https://huggingface.co/spaces/KPatrick/PaddleSpeechTTS) 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.
### Community
- Scan the QR code below with your Wechat (reply【语音】after your friend's application is approved), you can access to official technical exchange group. Look forward to your participation.
......@@ -327,7 +328,7 @@ PaddleSpeech supports a series of most popular models. They are summarized in [r
<th>Speech-to-Text Module Type</th>
<th>Dataset</th>
<th>Model Type</th>
<th>Link</th>
<th>Example</th>
</tr>
</thead>
<tbody>
......@@ -402,7 +403,7 @@ PaddleSpeech supports a series of most popular models. They are summarized in [r
<th> Text-to-Speech Module Type </th>
<th> Model Type </th>
<th> Dataset </th>
<th> Link </th>
<th> Example </th>
</tr>
</thead>
<tbody>
......@@ -520,7 +521,7 @@ PaddleSpeech supports a series of most popular models. They are summarized in [r
<th> Task </th>
<th> Dataset </th>
<th> Model Type </th>
<th> Link </th>
<th> Example </th>
</tr>
</thead>
<tbody>
......@@ -545,7 +546,7 @@ PaddleSpeech supports a series of most popular models. They are summarized in [r
<th> Task </th>
<th> Dataset </th>
<th> Model Type </th>
<th> Link </th>
<th> Example </th>
</tr>
</thead>
<tbody>
......@@ -570,7 +571,7 @@ PaddleSpeech supports a series of most popular models. They are summarized in [r
<th> Task </th>
<th> Dataset </th>
<th> Model Type </th>
<th> Link </th>
<th> Example </th>
</tr>
</thead>
<tbody>
......
......@@ -164,13 +164,17 @@ from https://github.com/18F/open-source-guide/blob/18f-pages/pages/making-readme
</div>
### 🔥 热门活动
- 2021.12.21~12.24
4 日直播课: 深度解读 PaddleSpeech 语音技术!
### 特性
**直播回放与课件资料: https://aistudio.baidu.com/aistudio/education/group/info/25130**
本项目采用了易用、高效、灵活以及可扩展的实现,旨在为工业应用、学术研究提供更好的支持,实现的功能包含训练、推断以及测试模块,以及部署过程,主要包括
- 📦 **易用性**: 安装门槛低,可使用 [CLI](#quick-start) 快速开始。
- 🏆 **对标 SoTA**: 提供了高速、轻量级模型,且借鉴了最前沿的技术。
- 🏆 **流式ASR和TTS系统**:工业级的端到端流式识别、流式合成系统。
- 💯 **基于规则的中文前端**: 我们的前端包含文本正则化和字音转换(G2P)。此外,我们使用自定义语言规则来适应中文语境。
- **多种工业界以及学术界主流功能支持**:
- 🛎️ 典型音频任务: 本工具包提供了音频任务如音频分类、语音翻译、自动语音识别、文本转语音、语音合成、声纹识别、KWS等任务的实现。
- 🔬 主流模型及数据集: 本工具包实现了参与整条语音任务流水线的各个模块,并且采用了主流数据集如 LibriSpeech、LJSpeech、AIShell、CSMSC,详情请见 [模型列表](#model-list)
- 🧩 级联模型应用: 作为传统语音任务的扩展,我们结合了自然语言处理、计算机视觉等任务,实现更接近实际需求的产业级应用。
### 近期更新
......@@ -178,23 +182,18 @@ from https://github.com/18F/open-source-guide/blob/18f-pages/pages/making-readme
<!---
2021.12.14: We would like to have an online courses to introduce basics and research of speech, as well as code practice with `paddlespeech`. Please pay attention to our [Calendar](https://www.paddlepaddle.org.cn/live).
--->
- 👏🏻 2022.04.28: PaddleSpeech Streaming Server 上线! 覆盖了语音识别和语音合成。
- 👏🏻 2022.03.28: PaddleSpeech Server 上线! 覆盖了声音分类、语音识别、以及语音合成。
- 👏🏻 2022.03.28: PaddleSpeech CLI 上线声纹验证。
- 🤗 2021.12.14: Our PaddleSpeech [ASR](https://huggingface.co/spaces/KPatrick/PaddleSpeechASR) and [TTS](https://huggingface.co/spaces/KPatrick/PaddleSpeechTTS) Demos on Hugging Face Spaces are available!
- 👏🏻 2021.12.10: PaddleSpeech CLI 上线!覆盖了声音分类、语音识别、语音翻译(英译中)以及语音合成。
- 👏🏻 2022.05.06: PaddleSpeech Streaming Server 上线! 覆盖了语音识别(标点恢复、时间戳),和语音合成。
- 👏🏻 2022.05.06: PaddleSpeech Server 上线! 覆盖了声音分类、语音识别、语音合成、声纹识别,标点恢复。
- 👏🏻 2022.03.28: PaddleSpeech CLI 覆盖声音分类、语音识别、语音翻译(英译中)、语音合成,声纹验证。
- 🤗 2021.12.14: PaddleSpeech [ASR](https://huggingface.co/spaces/KPatrick/PaddleSpeechASR) and [TTS](https://huggingface.co/spaces/KPatrick/PaddleSpeechTTS) Demos on Hugging Face Spaces are available!
### 🔥 热门活动
### 特性
- 2021.12.21~12.24
本项目采用了易用、高效、灵活以及可扩展的实现,旨在为工业应用、学术研究提供更好的支持,实现的功能包含训练、推断以及测试模块,以及部署过程,主要包括
- 📦 **易用性**: 安装门槛低,可使用 [CLI](#quick-start) 快速开始。
- 🏆 **对标 SoTA**: 提供了高速、轻量级模型,且借鉴了最前沿的技术。
- 💯 **基于规则的中文前端**: 我们的前端包含文本正则化和字音转换(G2P)。此外,我们使用自定义语言规则来适应中文语境。
- **多种工业界以及学术界主流功能支持**:
- 🛎️ 典型音频任务: 本工具包提供了音频任务如音频分类、语音翻译、自动语音识别、文本转语音、语音合成等任务的实现。
- 🔬 主流模型及数据集: 本工具包实现了参与整条语音任务流水线的各个模块,并且采用了主流数据集如 LibriSpeech、LJSpeech、AIShell、CSMSC,详情请见 [模型列表](#model-list)
- 🧩 级联模型应用: 作为传统语音任务的扩展,我们结合了自然语言处理、计算机视觉等任务,实现更接近实际需求的产业级应用。
4 日直播课: 深度解读 PaddleSpeech 语音技术!
**直播回放与课件资料: https://aistudio.baidu.com/aistudio/education/group/info/25130**
### 技术交流群
......@@ -328,8 +327,8 @@ PaddleSpeech 的 **语音转文本** 包含语音识别声学模型、语音识
<tr>
<th>语音转文本模块类型</th>
<th>数据集</th>
<th>模型种类</th>
<th>链接</th>
<th>模型类型</th>
<th>脚本</th>
</tr>
</thead>
<tbody>
......@@ -402,9 +401,9 @@ PaddleSpeech 的 **语音合成** 主要包含三个模块:文本前端、声
<thead>
<tr>
<th> 语音合成模块类型 </th>
<th> 模型种类 </th>
<th> 模型类型 </th>
<th> 数据集 </th>
<th> 链接 </th>
<th> 脚本 </th>
</tr>
</thead>
<tbody>
......@@ -520,8 +519,8 @@ PaddleSpeech 的 **语音合成** 主要包含三个模块:文本前端、声
<tr>
<th> 任务 </th>
<th> 数据集 </th>
<th> 模型种类 </th>
<th> 链接</th>
<th> 模型类型 </th>
<th> 脚本</th>
</tr>
</thead>
<tbody>
......@@ -544,10 +543,10 @@ PaddleSpeech 的 **语音合成** 主要包含三个模块:文本前端、声
<table style="width:100%">
<thead>
<tr>
<th> Task </th>
<th> Dataset </th>
<th> Model Type </th>
<th> Link </th>
<th> 任务 </th>
<th> 数据集 </th>
<th> 模型类型 </th>
<th> 脚本 </th>
</tr>
</thead>
<tbody>
......@@ -571,8 +570,8 @@ PaddleSpeech 的 **语音合成** 主要包含三个模块:文本前端、声
<tr>
<th> 任务 </th>
<th> 数据集 </th>
<th> 模型种类 </th>
<th> 链接 </th>
<th> 模型类型 </th>
<th> 脚本 </th>
</tr>
</thead>
<tbody>
......
......@@ -27,7 +27,7 @@ pretrained_models = {
'ckpt_path':
'exp/conformer/checkpoints/wenetspeech',
},
"conformer_online_wenetspeech-zh-16k": {
"conformer_online_wenetspeech-zh-16k": {
'url':
'https://paddlespeech.bj.bcebos.com/s2t/wenetspeech/asr1/asr1_chunk_conformer_wenetspeech_ckpt_1.0.0a.model.tar.gz',
'md5':
......
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