diff --git a/README.md b/README.md
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+++ b/README.md
@@ -115,13 +115,13 @@ 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.
-- 🏆 **Align to the State-of-the-Art**: we provide high-speed and ultra-lightweight models, and also cutting-edge technology. 
-- 💯 **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.
+- 📦  **Ease of Use**: low barriers to install, and [CLI](#quick-start) 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. 
+- 💯  **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.
-  - 🔬 *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).
+  - 🛎️  *Implementation of critical audio tasks*: this toolkit contains audio functions like  Audio Classification, Speech Translation, Automatic Speech Recognition, Text-to-Speech Synthesis, 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:
@@ -129,8 +129,8 @@ Via the easy-to-use, efficient, flexible and scalable implementation, our vision
 <!---
 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).
 --->
-- 🤗 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.
+- 🤗  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!
@@ -170,7 +170,7 @@ paddlespeech st --input input_16k.wav
 ```shell
 paddlespeech tts --input "你好，欢迎使用百度飞桨深度学习框架！" --output output.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: https://huggingface.co/spaces/akhaliq/paddlespeech
+- 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)
 
   
 If you want to try more functions like training and tuning, please have a look at [Speech-to-Text Quick Start](./docs/source/asr/quick_start.md) and [Text-to-Speech Quick Start](./docs/source/tts/quick_start.md).