游雁
2024-05-15 075d9117d9a2db57d46db669d2511a460275519e
docs
2个文件已修改
6 ■■■■ 已修改文件
README.md 2 ●●●●● 补丁 | 查看 | 原始文档 | blame | 历史
README_zh.md 4 ●●● 补丁 | 查看 | 原始文档 | blame | 历史
README.md
@@ -28,6 +28,7 @@
<a name="whats-new"></a>
## What's new:
- 2024/05/15:emotion recognition models are new supported. [emotion2vec+large](https://modelscope.cn/models/iic/emotion2vec_plus_large/summary),[emotion2vec+base](https://modelscope.cn/models/iic/emotion2vec_plus_base/summary),[emotion2vec+seed](https://modelscope.cn/models/iic/emotion2vec_plus_seed/summary). currently supports the following categories: 0: angry 1: happy 2: neutral 3: sad 4: unknown.
- 2024/05/15: Offline File Transcription Service 4.5, Offline File Transcription Service of English 1.6,Real-time Transcription Service 1.10 released,adapting to FunASR 1.0 model structure;([docs](runtime/readme.md))
- 2024/03/05:Added the Qwen-Audio and Qwen-Audio-Chat large-scale audio-text multimodal models, which have topped multiple audio domain leaderboards. These models support speech dialogue, [usage](examples/industrial_data_pretraining/qwen_audio).
- 2024/03/05:Added support for the Whisper-large-v3 model, a multitasking model that can perform multilingual speech recognition, speech translation, and language identification. It can be downloaded from the[modelscope](examples/industrial_data_pretraining/whisper/demo.py), and [openai](examples/industrial_data_pretraining/whisper/demo_from_openai.py).
@@ -88,6 +89,7 @@
|                                                Whisper-large-v3 <br> ([⭐](https://www.modelscope.cn/models/iic/Whisper-large-v3/summary)  [🍀](https://github.com/openai/whisper) )                                                 |  speech recognition, with timestamps, non-streaming   |          multilingual            |    1550 M    |
|                                         Qwen-Audio <br> ([⭐](examples/industrial_data_pretraining/qwen_audio/demo.py)  [🤗](https://huggingface.co/Qwen/Qwen-Audio) )                                         |      audio-text multimodal models (pretraining)       |     multilingual      |  8B  |
|                   Qwen-Audio-Chat <br> ([⭐](examples/industrial_data_pretraining/qwen_audio/demo_chat.py)  [🤗](https://huggingface.co/Qwen/Qwen-Audio-Chat) )                                                |          audio-text multimodal models (chat)          |     multilingual      |  8B  |
|                        emotion2vec+large <br> ([⭐](https://modelscope.cn/models/iic/emotion2vec_plus_large/summary)  [🤗](https://huggingface.co/emotion2vec/emotion2vec_plus_large) )                        |              speech emotion recongintion              |           40000 hours            |  300M  |
README_zh.md
@@ -29,6 +29,7 @@
<a name="最新动态"></a>
## 最新动态
- 2024/05/15:新增加情感识别模型,[emotion2vec+large](https://modelscope.cn/models/iic/emotion2vec_plus_large/summary),[emotion2vec+base](https://modelscope.cn/models/iic/emotion2vec_plus_base/summary),[emotion2vec+seed](https://modelscope.cn/models/iic/emotion2vec_plus_seed/summary),输出情感类别为:生气/angry,开心/happy,中立/neutral,难过/sad。
- 2024/05/15: 中文离线文件转写服务 4.5、英文离线文件转写服务 1.6、中文实时语音听写服务 1.10 发布,适配FunASR 1.0模型结构;详细信息参阅([部署文档](runtime/readme_cn.md))
- 2024/03/05:新增加Qwen-Audio与Qwen-Audio-Chat音频文本模态大模型,在多个音频领域测试榜单刷榜,中支持语音对话,详细用法见 [示例](examples/industrial_data_pretraining/qwen_audio)。
- 2024/03/05:新增加Whisper-large-v3模型支持,多语言语音识别/翻译/语种识别,支持从 [modelscope](examples/industrial_data_pretraining/whisper/demo.py)仓库下载,也支持从 [openai](examples/industrial_data_pretraining/whisper/demo_from_openai.py)仓库下载模型。
@@ -76,7 +77,7 @@
|                                                                                                     模型名字                                                                                                      |        任务详情        |     训练数据     | 参数量  | 
|:-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------:|:------------------:|:------------:|:----:|
|:-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------:|:------------------:|:--------------:|:------:|
|    paraformer-zh <br> ([⭐](https://www.modelscope.cn/models/damo/speech_paraformer-large-vad-punc_asr_nat-zh-cn-16k-common-vocab8404-pytorch/summary)  [🤗](https://huggingface.co/funasr/paraformer-tp) )    |  语音识别,带时间戳输出,非实时   |  60000小时,中文  | 220M |
| paraformer-zh-streaming <br> ( [⭐](https://modelscope.cn/models/damo/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-online/summary) [🤗](https://huggingface.co/funasr/paraformer-zh-streaming) ) |      语音识别,实时       |  60000小时,中文  | 220M |
|         paraformer-en <br> ( [⭐](https://www.modelscope.cn/models/damo/speech_paraformer-large-vad-punc_asr_nat-en-16k-common-vocab10020/summary) [🤗](https://huggingface.co/funasr/paraformer-en) )         |      语音识别,非实时      |  50000小时,英文  | 220M |
@@ -88,6 +89,7 @@
|                                     Whisper-large-v3 <br> ([⭐](https://www.modelscope.cn/models/iic/Whisper-large-v3/summary)  [🍀](https://github.com/openai/whisper) )                                      |  语音识别,带时间戳输出,非实时   |     多语言      |  1550 M  |
|                                         Qwen-Audio <br> ([⭐](examples/industrial_data_pretraining/qwen_audio/demo.py)  [🤗](https://huggingface.co/Qwen/Qwen-Audio) )                                         |  音频文本多模态大模型(预训练)   |     多语言      |  8B  |
|                   Qwen-Audio-Chat <br> ([⭐](examples/industrial_data_pretraining/qwen_audio/demo_chat.py)  [🤗](https://huggingface.co/Qwen/Qwen-Audio-Chat) )                                                | 音频文本多模态大模型(chat版本) |     多语言      |  8B  |
|                        emotion2vec+large <br> ([⭐](https://modelscope.cn/models/iic/emotion2vec_plus_large/summary)  [🤗](https://huggingface.co/emotion2vec/emotion2vec_plus_large) )                        |    情感识别模型          | 40000小时,4种情感类别 |  300M  |
<a name="快速开始"></a>
## 快速开始