From 497b68b28bb8da06f6cff372c40b76de9b05587d Mon Sep 17 00:00:00 2001
From: 游雁 <zhifu.gzf@alibaba-inc.com>
Date: 星期四, 20 七月 2023 19:06:46 +0800
Subject: [PATCH] docs

---
 README_zh.md |    3 +
 README.md    |  108 ++++++++++++++++++++++++++++++++++++++++-------------
 2 files changed, 83 insertions(+), 28 deletions(-)

diff --git a/README.md b/README.md
index 46741fa..e304da0 100644
--- a/README.md
+++ b/README.md
@@ -23,18 +23,43 @@
 <a name="whats-new"></a>
 ## What's new: 
 
-### FunASR runtime-SDK
+### FunASR runtime
 
 - 2023.07.03: 
 We have release the FunASR runtime-SDK-0.1.0, file transcription service (Mandarin) is now supported ([ZH](funasr/runtime/readme_cn.md)/[EN](funasr/runtime/readme.md))
 
 ### Multi-Channel Multi-Party Meeting Transcription 2.0 (M2MeT2.0) Challenge
 
-We are pleased to announce that the M2MeT2.0 challenge has been accepted by the ASRU 2023 challenge special session. The registration is now open. The baseline system is conducted on FunASR and is provided as a receipe of AliMeeting corpus. For more details you can see the guidence of M2MET2.0 ([CN](https://alibaba-damo-academy.github.io/FunASR/m2met2_cn/index.html)/[EN](https://alibaba-damo-academy.github.io/FunASR/m2met2/index.html)).
+Challenge details ref to ([CN](https://alibaba-damo-academy.github.io/FunASR/m2met2_cn/index.html)/[EN](https://alibaba-damo-academy.github.io/FunASR/m2met2/index.html))
 
-### Release notes
+### Speech Recognition
+ 
+- Academic Models
+  - Encoder-Decoder Models (AED): [Transformer](egs/aishell/transformer), [Conformer](egs/aishell/conformer), [Branchformer](egs/aishell/branchformer)
+  - Transducer Models (RNNT): [RNNT streaming](egs/aishell/rnnt), [BAT streaming/non-streaming](egs/aishell/bat)
+  - Non-autoregressive Model (NAR): [Paraformer](egs/aishell/paraformer)
+  - Multi-speaker recognition model: [MFCCA](egs_modelscope/asr/mfcca)
 
-For the release notes, please ref to [news](https://github.com/alibaba-damo-academy/FunASR/releases)
+
+- Industrial-level Models
+  - Paraformer Models (Mandarin): [Paraformer-large](egs_modelscope/asr/paraformer/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-pytorch), [Paraformer-large-long](egs_modelscope/asr_vad_punc/speech_paraformer-large-vad-punc_asr_nat-zh-cn-16k-common-vocab8404-pytorch), [Paraformer-large streaming](egs_modelscope/asr/paraformer/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-online), [Paraformer-large-contextual](egs_modelscope/asr/paraformer/speech_paraformer-large-contextual_asr_nat-zh-cn-16k-common-vocab8404)
+  - Conformer Models (English): [Conformer]()
+  - UniASR streaming offline unifying models: [16k UniASR Burmese](https://modelscope.cn/models/damo/speech_UniASR_asr_2pass-my-16k-common-vocab696-pytorch/summary), [16k UniASR Hebrew](https://modelscope.cn/models/damo/speech_UniASR_asr_2pass-he-16k-common-vocab1085-pytorch/summary), [16k UniASR Urdu](https://modelscope.cn/models/damo/speech_UniASR_asr_2pass-ur-16k-common-vocab877-pytorch/summary), [8k UniASR Mandarin financial domain](https://www.modelscope.cn/models/damo/speech_UniASR_asr_2pass-zh-cn-8k-finance-vocab3445-online/summary), [16k UniASR Mandarin audio-visual domain](https://www.modelscope.cn/models/damo/speech_UniASR_asr_2pass-zh-cn-16k-audio_and_video-vocab3445-online/summary),
+  [Southern Fujian Dialect model](https://modelscope.cn/models/damo/speech_UniASR_asr_2pass-minnan-16k-common-vocab3825/summary), [French model](https://modelscope.cn/models/damo/speech_UniASR_asr_2pass-fr-16k-common-vocab3472-tensorflow1-online/summary),  [German model](https://modelscope.cn/models/damo/speech_UniASR_asr_2pass-de-16k-common-vocab3690-tensorflow1-online/summary),  [Vietnamese model](https://modelscope.cn/models/damo/speech_UniASR_asr_2pass-vi-16k-common-vocab1001-pytorch-online/summary),  [Persian model](https://modelscope.cn/models/damo/speech_UniASR_asr_2pass-fa-16k-common-vocab1257-pytorch-online/summary)
+
+- Speaker Recognition
+  - Speaker Verification Model: [xvector](egs_modelscope/speaker_verification)
+  - Speaker Diarization Model: [SOND](egs/callhome/diarization/sond)
+
+- Punctuation Restoration
+  - Chinese Punctuation Model: [CT-Transformer](egs_modelscope/punctuation/punc_ct-transformer_zh-cn-common-vocab272727-pytorch), [CT-Transformer streaming](egs_modelscope/punctuation/punc_ct-transformer_zh-cn-common-vadrealtime-vocab272727)
+
+- Endpoint Detection
+  - [FSMN-VAD](egs_modelscope/vad/speech_fsmn_vad_zh-cn-16k-common)
+
+- Timestamp Prediction
+  - Character-level FA Model: [TP-Aligner](egs_modelscope/tp/speech_timestamp_prediction-v1-16k-offline)
+
 
 <a name="highlights"></a>
 ## Highlights
@@ -75,22 +100,57 @@
 <a name="quick-start"></a>
 ## Quick Start
 
-You could use FunASR by:
+You can use FunASR in the following ways:
 
-- egs
-- egs_modelscope
-- runtime
+- Service Deployment SDK
+- Industrial model egs
+- Academic model egs
 
-### egs
-If you want to train the model from scratch, you could use funasr directly by recipe, as the following:
+### Service Deployment SDK
+
+#### Python version Example
+Supports real-time streaming speech recognition, uses non-streaming models for error correction, and outputs text with punctuation. Currently, only single client is supported. For multi-concurrency, please refer to the C++ version service deployment SDK below.
+
+##### Server Deployment
+
 ```shell
-cd egs/aishell/paraformer
-. ./run.sh --CUDA_VISIBLE_DEVICES="0,1" --gpu_num=2
+cd funasr/runtime/python/websocket
+python funasr_wss_server.py --port 10095
 ```
-More examples could be found in [docs](https://alibaba-damo-academy.github.io/FunASR/en/modelscope_pipeline/quick_start.html)
 
-### egs_modelscope
-If you want to infer or finetune pretraining models from modelscope, you could use funasr by modelscope pipeline, as the following:
+##### Client Testing
+
+```shell
+python funasr_wss_client.py --host "127.0.0.1" --port 10095 --mode 2pass --chunk_size "5,10,5"
+```
+
+For more examples, please refer to [docs](https://alibaba-damo-academy.github.io/FunASR/en/runtime/websocket_python.html#id2).
+
+#### C++ version Example
+
+Currently, offline file transcription service (CPU) is supported, and concurrent requests of hundreds of channels are supported.
+
+##### Server Deployment
+
+You can use the following command to complete the deployment with one click:
+
+```shell
+curl -O https://isv-data.oss-cn-hangzhou.aliyuncs.com/ics/MaaS/ASR/shell/funasr-runtime-deploy-offline-cpu-zh.sh
+sudo bash funasr-runtime-deploy-offline-cpu-zh.sh install --workspace ./funasr-runtime-resources
+```
+
+##### Client Testing
+
+```shell
+python3 funasr_wss_client.py --host "127.0.0.1" --port 10095 --mode offline --audio_in "../audio/asr_example.wav"
+```
+
+For more examples, please refer to [docs](https://github.com/alibaba-damo-academy/FunASR/blob/main/funasr/runtime/docs/SDK_tutorial_zh.md)
+
+
+### Industrial Model Egs
+
+If you want to use the pre-trained industrial models in ModelScope for inference or fine-tuning training, you can refer to the following command:
 
 ```python
 from modelscope.pipelines import pipeline
@@ -105,24 +165,18 @@
 print(rec_result)
 # {'text': '娆㈣繋澶у鏉ヤ綋楠岃揪鎽╅櫌鎺ㄥ嚭鐨勮闊宠瘑鍒ā鍨�'}
 ```
+
 More examples could be found in [docs](https://alibaba-damo-academy.github.io/FunASR/en/modelscope_pipeline/quick_start.html)
 
-### runtime
+### Academic model egs
 
-An example with websocket:
+If you want to train from scratch, usually for academic models, you can start training and inference with the following command:
 
-For the server:
 ```shell
-cd funasr/runtime/python/websocket
-python funasr_wss_server.py --port 10095
+cd egs/aishell/paraformer
+. ./run.sh --CUDA_VISIBLE_DEVICES="0,1" --gpu_num=2
 ```
-
-For the client:
-```shell
-python funasr_wss_client.py --host "127.0.0.1" --port 10095 --mode 2pass --chunk_size "5,10,5"
-#python funasr_wss_client.py --host "127.0.0.1" --port 10095 --mode 2pass --chunk_size "8,8,4" --audio_in "./data/wav.scp" --output_dir "./results"
-```
-More examples could be found in [docs](https://alibaba-damo-academy.github.io/FunASR/en/runtime/websocket_python.html#id2)
+More examples could be found in [docs](https://alibaba-damo-academy.github.io/FunASR/en/modelscope_pipeline/quick_start.html)
 
 <a name="contact"></a>
 ## Contact
diff --git a/README_zh.md b/README_zh.md
index ef5cfa6..ee9342d 100644
--- a/README_zh.md
+++ b/README_zh.md
@@ -49,7 +49,8 @@
   - 涓枃閫氱敤妯″瀷锛歔Paraformer-large](egs_modelscope/asr/paraformer/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-pytorch)锛孾Paraformer-large闀块煶棰戠増鏈琞(egs_modelscope/asr_vad_punc/speech_paraformer-large-vad-punc_asr_nat-zh-cn-16k-common-vocab8404-pytorch)锛孾Paraformer-large娴佸紡鐗堟湰](egs_modelscope/asr/paraformer/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-online)
   - 涓枃閫氱敤鐑瘝妯″瀷锛歔Paraformer-large-contextual](egs_modelscope/asr/paraformer/speech_paraformer-large-contextual_asr_nat-zh-cn-16k-common-vocab8404)锛�
   - 鑻辨枃閫氱敤妯″瀷锛歔Conformer]()
-  - 娴佸紡绂荤嚎涓�浣撳寲妯″瀷锛歔UniASR]()
+  - 娴佸紡绂荤嚎涓�浣撳寲妯″瀷锛� [16k UniASR闂藉崡璇璢(https://modelscope.cn/models/damo/speech_UniASR_asr_2pass-minnan-16k-common-vocab3825/summary)銆� [16k UniASR娉曡](https://modelscope.cn/models/damo/speech_UniASR_asr_2pass-fr-16k-common-vocab3472-tensorflow1-online/summary)銆� [16k UniASR寰疯](https://modelscope.cn/models/damo/speech_UniASR_asr_2pass-de-16k-common-vocab3690-tensorflow1-online/summary)銆� [16k UniASR瓒婂崡璇璢(https://modelscope.cn/models/damo/speech_UniASR_asr_2pass-vi-16k-common-vocab1001-pytorch-online/summary)銆� [16k UniASR娉㈡柉璇璢(https://modelscope.cn/models/damo/speech_UniASR_asr_2pass-fa-16k-common-vocab1257-pytorch-online/summary),
+  [16k UniASR缂呯敻璇璢(https://modelscope.cn/models/damo/speech_UniASR_asr_2pass-my-16k-common-vocab696-pytorch/summary)銆�      [16k UniASR甯屼集鏉ヨ](https://modelscope.cn/models/damo/speech_UniASR_asr_2pass-he-16k-common-vocab1085-pytorch/summary)銆�      [16k UniASR涔屽皵閮借](https://modelscope.cn/models/damo/speech_UniASR_asr_2pass-ur-16k-common-vocab877-pytorch/summary)銆�      [8k UniASR涓枃閲戣瀺棰嗗煙](https://www.modelscope.cn/models/damo/speech_UniASR_asr_2pass-zh-cn-8k-finance-vocab3445-online/summary)銆乕16k UniASR涓枃闊宠棰戦鍩焆(https://www.modelscope.cn/models/damo/speech_UniASR_asr_2pass-zh-cn-16k-audio_and_video-vocab3445-online/summary)
     
 ### 璇磋瘽浜鸿瘑鍒�
   - 璇磋瘽浜虹‘璁ゆā鍨嬶細[xvector](egs_modelscope/speaker_verification)

--
Gitblit v1.9.1