From 6d3a3da8a8c7d1be9740a9b2d6fac767f8dfff17 Mon Sep 17 00:00:00 2001
From: 游雁 <zhifu.gzf@alibaba-inc.com>
Date: 星期四, 30 五月 2024 19:16:52 +0800
Subject: [PATCH] docs
---
README.md | 34 ++++++++++++++++++++++++++++++----
1 files changed, 30 insertions(+), 4 deletions(-)
diff --git a/README.md b/README.md
index 81fb1b3..c9eae96 100644
--- a/README.md
+++ b/README.md
@@ -2,8 +2,9 @@
([绠�浣撲腑鏂嘳(./README_zh.md)|English)
-# FunASR: A Fundamental End-to-End Speech Recognition Toolkit
+[//]: # (# FunASR: A Fundamental End-to-End Speech Recognition Toolkit)
+[](https://github.com/Akshay090/svg-banners)
[](https://pypi.org/project/funasr/)
@@ -59,18 +60,26 @@
<a name="Installation"></a>
## Installation
+- Requirements
+```text
+python>=3.8
+torch>=1.13
+torchaudio
+```
+
+- Install for pypi
```shell
pip3 install -U funasr
```
-Or install from source code
+- Or install from source code
``` sh
git clone https://github.com/alibaba/FunASR.git && cd FunASR
pip3 install -e ./
```
-Install modelscope for the pretrained models (Optional)
+- Install modelscope or huggingface_hub for the pretrained models (Optional)
```shell
-pip3 install -U modelscope
+pip3 install -U modelscope huggingface_hub
```
## Model Zoo
@@ -157,6 +166,8 @@
```
Note: `chunk_size` is the configuration for streaming latency.` [0,10,5]` indicates that the real-time display granularity is `10*60=600ms`, and the lookahead information is `5*60=300ms`. Each inference input is `600ms` (sample points are `16000*0.6=960`), and the output is the corresponding text. For the last speech segment input, `is_final=True` needs to be set to force the output of the last word.
+<details><summary>More Examples</summary>
+
### Voice Activity Detection (Non-Streaming)
```python
from funasr import AutoModel
@@ -215,9 +226,24 @@
res = model.generate(input=(wav_file, text_file), data_type=("sound", "text"))
print(res)
```
+
+
+### Speech Emotion Recognition
+```python
+from funasr import AutoModel
+
+model = AutoModel(model="emotion2vec_plus_large")
+
+wav_file = f"{model.model_path}/example/test.wav"
+
+res = model.generate(wav_file, output_dir="./outputs", granularity="utterance", extract_embedding=False)
+print(res)
+```
+
More usages ref to [docs](docs/tutorial/README_zh.md),
more examples ref to [demo](https://github.com/alibaba-damo-academy/FunASR/tree/main/examples/industrial_data_pretraining)
+</details>
## Export ONNX
--
Gitblit v1.9.1