From f932e01d36065c1d320758c16ced268085f90601 Mon Sep 17 00:00:00 2001
From: 游雁 <zhifu.gzf@alibaba-inc.com>
Date: 星期五, 31 五月 2024 11:30:30 +0800
Subject: [PATCH] docs

---
 README.md |   12 ++++++------
 1 files changed, 6 insertions(+), 6 deletions(-)

diff --git a/README.md b/README.md
index c9eae96..835eed4 100644
--- a/README.md
+++ b/README.md
@@ -94,15 +94,15 @@
 | <nobr>paraformer-zh-streaming <br> ( [猸怾(https://modelscope.cn/models/damo/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-online/summary) [馃](https://huggingface.co/funasr/paraformer-zh-streaming) )</nobr> |             speech recognition, streaming             |      60000 hours, Mandarin       |    220M    |
 |               paraformer-en <br> ( [猸怾(https://www.modelscope.cn/models/damo/speech_paraformer-large-vad-punc_asr_nat-en-16k-common-vocab10020/summary) [馃](https://huggingface.co/funasr/paraformer-en) )                | speech recognition, without timestamps, non-streaming |       50000 hours, English       |    220M    |
 |                            conformer-en <br> ( [猸怾(https://modelscope.cn/models/damo/speech_conformer_asr-en-16k-vocab4199-pytorch/summary) [馃](https://huggingface.co/funasr/conformer-en) )                             |           speech recognition, non-streaming           |       50000 hours, English       |    220M    |
-|                               ct-punc <br> ( [猸怾(https://modelscope.cn/models/damo/punc_ct-transformer_cn-en-common-vocab471067-large/summary) [馃](https://huggingface.co/funasr/ct-punc) )                               |                punctuation restoration                |    100M, Mandarin and English    |    1.1G    | 
+|                               ct-punc <br> ( [猸怾(https://modelscope.cn/models/damo/punc_ct-transformer_cn-en-common-vocab471067-large/summary) [馃](https://huggingface.co/funasr/ct-punc) )                               |                punctuation restoration                |    100M, Mandarin and English    |    290M    | 
 |                                   fsmn-vad <br> ( [猸怾(https://modelscope.cn/models/damo/speech_fsmn_vad_zh-cn-16k-common-pytorch/summary) [馃](https://huggingface.co/funasr/fsmn-vad) )                                   |               voice activity detection                | 5000 hours, Mandarin and English |    0.4M    | 
 |                                     fa-zh <br> ( [猸怾(https://modelscope.cn/models/damo/speech_timestamp_prediction-v1-16k-offline/summary) [馃](https://huggingface.co/funasr/fa-zh) )                                     |                 timestamp prediction                  |       5000 hours, Mandarin       |    38M     | 
 |                                       cam++ <br> ( [猸怾(https://modelscope.cn/models/iic/speech_campplus_sv_zh-cn_16k-common/summary) [馃](https://huggingface.co/funasr/campplus) )                                        |           speaker verification/diarization            |            5000 hours            |    7.2M    | 
-|                                 Whisper-large-v2 <br> ([猸怾(https://www.modelscope.cn/models/iic/speech_whisper-large_asr_multilingual/summary)  [馃崁](https://github.com/openai/whisper) )                                  |  speech recognition, with timestamps, non-streaming   |           multilingual           |    1550 M    |
-|                                            Whisper-large-v3 <br> ([猸怾(https://www.modelscope.cn/models/iic/Whisper-large-v3/summary)  [馃崁](https://github.com/openai/whisper) )                                            |  speech recognition, with timestamps, non-streaming   |           multilingual           |    1550 M    |
-|                                               Qwen-Audio <br> ([猸怾(examples/industrial_data_pretraining/qwen_audio/demo.py)  [馃](https://huggingface.co/Qwen/Qwen-Audio) )                                                |      audio-text multimodal models (pretraining)       |           multilingual           |  8B  |
-|                                        Qwen-Audio-Chat <br> ([猸怾(examples/industrial_data_pretraining/qwen_audio/demo_chat.py)  [馃](https://huggingface.co/Qwen/Qwen-Audio-Chat) )                                        |          audio-text multimodal models (chat)          |           multilingual           |  8B  |
-|                              emotion2vec+large <br> ([猸怾(https://modelscope.cn/models/iic/emotion2vec_plus_large/summary)  [馃](https://huggingface.co/emotion2vec/emotion2vec_plus_large) )                               |              speech emotion recongintion              |           40000 hours            |  300M  |
+|                                 Whisper-large-v2 <br> ([猸怾(https://www.modelscope.cn/models/iic/speech_whisper-large_asr_multilingual/summary)  [馃崁](https://github.com/openai/whisper) )                                  |  speech recognition, with timestamps, non-streaming   |           multilingual           |   1550 M   |
+|                                            Whisper-large-v3 <br> ([猸怾(https://www.modelscope.cn/models/iic/Whisper-large-v3/summary)  [馃崁](https://github.com/openai/whisper) )                                            |  speech recognition, with timestamps, non-streaming   |           multilingual           |   1550 M   |
+|                                               Qwen-Audio <br> ([猸怾(examples/industrial_data_pretraining/qwen_audio/demo.py)  [馃](https://huggingface.co/Qwen/Qwen-Audio) )                                                |      audio-text multimodal models (pretraining)       |           multilingual           |     8B     |
+|                                        Qwen-Audio-Chat <br> ([猸怾(examples/industrial_data_pretraining/qwen_audio/demo_chat.py)  [馃](https://huggingface.co/Qwen/Qwen-Audio-Chat) )                                        |          audio-text multimodal models (chat)          |           multilingual           |     8B     |
+|                              emotion2vec+large <br> ([猸怾(https://modelscope.cn/models/iic/emotion2vec_plus_large/summary)  [馃](https://huggingface.co/emotion2vec/emotion2vec_plus_large) )                               |              speech emotion recongintion              |           40000 hours            |    300M    |
 
 
 

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