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https://github.com/modelscope/FunASR
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@ -24,7 +24,18 @@ FunASR hopes to build a bridge between academic research and industrial applicat
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.. toctree::
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:maxdepth: 1
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:caption: ModelScope:
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:caption: Runtime:
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../funasr/export/README.md
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../funasr/runtime/python/onnxruntime/README.md
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../funasr/runtime/python/libtorch/README.md
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../funasr/runtime/onnxruntime/readme.md
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../funasr/runtime/grpc/Readme.md
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.. toctree::
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:maxdepth: 1
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:caption: ModelScope pipeline:
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./modelscope_models.md
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./modelscope_usages.md
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@ -1,4 +1,4 @@
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# Pretrained models on ModelScope
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# Pretrained models
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## Model License
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- Apache License 2.0
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@ -27,8 +27,8 @@ Here we provided several pretrained models on different datasets. The details of
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| Model Name | Language | Training Data | Vocab Size | Parameter | Offline/Online | Notes |
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|:--------------------------------------------------------------------------------------------------------------------------------------:|:--------:|:--------------------------------:|:----------:|:---------:|:--------------:|:--------------------------------------------------------------------------------------------------------------------------------|
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| [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 |
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| [UniASR-large](https://modelscope.cn/models/damo/speech_UniASR-large_asr_2pass-zh-cn-16k-common-vocab8358-tensorflow1-offline/summary) | CN, EN | Alibaba Speech Data (60000hours) | 8358 | 220M | Offline | UniASR streaming offline unifying models |
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| [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 |
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| [UniASR-large](https://modelscope.cn/models/damo/speech_UniASR-large_asr_2pass-zh-cn-16k-common-vocab8358-tensorflow1-offline/summary) | CN & EN | Alibaba Speech Data (60000hours) | 8358 | 220M | Offline | UniASR streaming offline unifying models |
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| [UniASR Burmese](https://modelscope.cn/models/damo/speech_UniASR_asr_2pass-my-16k-common-vocab696-pytorch/summary) | Burmese | Alibaba Speech Data (? hours) | 696 | 95M | Online | UniASR streaming offline unifying models |
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| [UniASR Hebrew](https://modelscope.cn/models/damo/speech_UniASR_asr_2pass-he-16k-common-vocab1085-pytorch/summary) | Hebrew | Alibaba Speech Data (? hours) | 1085 | 95M | Online | UniASR streaming offline unifying models |
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| [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 |
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@ -47,9 +47,9 @@ Here we provided several pretrained models on different datasets. The details of
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#### MFCCA Models
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| Model Name | Language | Training Data | Vocab Size | Parameter | Offline/Online | Notes |
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|:----------------------------------------------------------------------------------------------------------------------:|:--------:|:---------------------:|:----------:|:---------:|:--------------:|:--------------------------------------------------------------------------------------------------------------------------------|
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| [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
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| Model Name | Language | Training Data | Vocab Size | Parameter | Offline/Online | Notes |
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|:-------------------------------------------------------------------------------------------------------------:|:--------:|:------------------------------------------:|:----------:|:---------:|:--------------:|:--------------------------------------------------------------------------------------------------------------------------------|
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| [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 |
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