Update modelscope_models.md

docs/modelscope_models.md

@@ -8,6 +8,7 @@ Here we provided several pretrained models on different datasets. The details of
 
 ### Speech Recognition Models
 #### Paraformer Models
+
 |                                                                     Model Name                                                                     | Language |          Training Data           | Vocab Size | Parameter | Offline/Online | Notes                                                                                                                           |
 |:--------------------------------------------------------------------------------------------------------------------------------------------------:|:--------:|:--------------------------------:|:----------:|:---------:|:--------------:|:--------------------------------------------------------------------------------------------------------------------------------|
 |        [Paraformer-large](https://www.modelscope.cn/models/damo/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-pytorch/summary)        | CN & EN  | Alibaba Speech Data (60000hours) |    8404    |   220M    |    Offline     | Duration of input wav <= 20s                                                                                                    |
@@ -23,6 +24,7 @@ Here we provided several pretrained models on different datasets. The details of
 
 
 #### UniASR Models
+
 |                                                               Model Name                                                               | Language |          Training Data           | Vocab Size | Parameter | Offline/Online | Notes                                                                                                                           |
 |:--------------------------------------------------------------------------------------------------------------------------------------:|:--------:|:--------------------------------:|:----------:|:---------:|:--------------:|:--------------------------------------------------------------------------------------------------------------------------------|
 |       [UniASR](https://modelscope.cn/models/damo/speech_UniASR_asr_2pass-zh-cn-16k-common-vocab8358-tensorflow1-online/summary)        | CN, EN  | Alibaba Speech Data (60000hours) |    8358    |   100M    |     Online     | UniASR streaming offline unifying models                                                                                                    |
@@ -32,12 +34,14 @@ Here we provided several pretrained models on different datasets. The details of
 |       [UniASR Urdu](https://modelscope.cn/models/damo/speech_UniASR_asr_2pass-ur-16k-common-vocab877-pytorch/summary)                  |   Urdu   |  Alibaba Speech Data (? hours)   |    877     |    95M    |     Online     | UniASR streaming offline unifying models                                                                                                    |
 
 #### Conformer Models
+
 |                                                       Model Name                                                       | Language |     Training Data     | Vocab Size | Parameter | Offline/Online | Notes                                                                                                                           |
 |:----------------------------------------------------------------------------------------------------------------------:|:--------:|:---------------------:|:----------:|:---------:|:--------------:|:--------------------------------------------------------------------------------------------------------------------------------|
 | [Conformer](https://modelscope.cn/models/damo/speech_conformer_asr_nat-zh-cn-16k-aishell1-vocab4234-pytorch/summary)   |   CN     |  AISHELL (178hours)   |    4234    |    44M    |    Offline     | Duration of input wav <= 20s                                                                                                    |
 | [Conformer](https://www.modelscope.cn/models/damo/speech_conformer_asr_nat-zh-cn-16k-aishell2-vocab5212-pytorch/summary)   |   CN     | AISHELL-2 (1000hours) |    5212    |    44M    |    Offline     | Duration of input wav <= 20s                                                                                                    |
 
 #### MFCCA Models
+
 |                                                       Model Name                                                       | Language |     Training Data     | Vocab Size | Parameter | Offline/Online | Notes                                                                                                                           |
 |:----------------------------------------------------------------------------------------------------------------------:|:--------:|:---------------------:|:----------:|:---------:|:--------------:|:--------------------------------------------------------------------------------------------------------------------------------|
 | [MFCCA](https://www.modelscope.cn/models/NPU-ASLP/speech_mfcca_asr-zh-cn-16k-alimeeting-vocab4950/summary)   |   CN     |  AliMeeting、AISHELL-4、Simudata (917hours)   |    4950    |    45M    |    Offline     | Duration of input wav <= 20s, channel of input wav <= 8 channel