From 07be725277aedf16d1dd5f6248d3a1d6001de4d1 Mon Sep 17 00:00:00 2001 From: zhifu gao <zhifu.gzf@alibaba-inc.com> Date: 星期五, 14 七月 2023 13:03:12 +0800 Subject: [PATCH] Update readme_zh.md --- docs/model_zoo/modelscope_models.md | 6 ++++-- 1 files changed, 4 insertions(+), 2 deletions(-) diff --git a/docs/model_zoo/modelscope_models.md b/docs/model_zoo/modelscope_models.md index 8fe4e05..a9fc52e 100644 --- a/docs/model_zoo/modelscope_models.md +++ b/docs/model_zoo/modelscope_models.md @@ -1,8 +1,10 @@ # Pretrained Models on ModelScope ## Model License -You are free to use, copy, modify, and share FunASR under the conditions of this agreement. You should indicate the code and model source and author information when using, copying, modifying and sharing FunASR. To upload the FunASR industrial model to any third-party platform for download and use, an additional license is required, which can be applied for free by sending an email to the official email address (funasr@list.alibaba-inc.com). Full license could see [license](https://github.com/alibaba-damo-academy/FunASR/blob/main/LICENSE) +You are free to use, copy, modify, and share FunASR models under the conditions of this agreement. You should indicate the model source and author information when using, copying, modifying and sharing FunASR models. You should keep the relevant names of models in [FunASR software].. Full model license could see [license](https://github.com/alibaba-damo-academy/FunASR/blob/main/MODEL_LICENSE) +## Model Usage +Ref to [docs](https://alibaba-damo-academy.github.io/FunASR/en/modelscope_pipeline/quick_start.html) ## Model Zoo Here we provided several pretrained models on different datasets. The details of models and datasets can be found on [ModelScope](https://www.modelscope.cn/models?page=1&tasks=auto-speech-recognition). @@ -13,7 +15,7 @@ | 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 | -| [Paraformer-large-long](https://www.modelscope.cn/models/damo/speech_paraformer-large-vad-punc_asr_nat-zh-cn-16k-common-vocab8404-pytorch/summary) | CN & EN | Alibaba Speech Data (60000hours) | 8404 | 220M | Offline | Which ould deal with arbitrary length input wav | +| [Paraformer-large-long](https://www.modelscope.cn/models/damo/speech_paraformer-large-vad-punc_asr_nat-zh-cn-16k-common-vocab8404-pytorch/summary) | CN & EN | Alibaba Speech Data (60000hours) | 8404 | 220M | Offline | Which would deal with arbitrary length input wav | | [Paraformer-large-contextual](https://www.modelscope.cn/models/damo/speech_paraformer-large-contextual_asr_nat-zh-cn-16k-common-vocab8404/summary) | CN & EN | Alibaba Speech Data (60000hours) | 8404 | 220M | Offline | Which supports the hotword customization based on the incentive enhancement, and improves the recall and precision of hotwords. | | [Paraformer](https://modelscope.cn/models/damo/speech_paraformer_asr_nat-zh-cn-16k-common-vocab8358-tensorflow1/summary) | CN & EN | Alibaba Speech Data (50000hours) | 8358 | 68M | Offline | Duration of input wav <= 20s | | [Paraformer-online](https://www.modelscope.cn/models/damo/speech_paraformer_asr_nat-zh-cn-16k-common-vocab8404-online/summary) | CN & EN | Alibaba Speech Data (50000hours) | 8404 | 68M | Online | Which could deal with streaming input | -- Gitblit v1.9.1