sugarcase
2024-09-25 8cd8e25f180b57c74f1ae7fd39001e5af4c20f8b
README.md
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<a name="whats-new"></a>
## What's new:
- 2024/09/25:keyword spotting models are new supported. Supports fine-tuning and inference for four models: [fsmn_kws](https://modelscope.cn/models/iic/speech_sanm_kws_phone-xiaoyun-commands-online), [fsmn_kws_mt](https://modelscope.cn/models/iic/speech_sanm_kws_phone-xiaoyun-commands-online), [sanm_kws](https://modelscope.cn/models/iic/speech_sanm_kws_phone-xiaoyun-commands-offline), [sanm_kws_streaming](https://modelscope.cn/models/iic/speech_sanm_kws_phone-xiaoyun-commands-online).
- 2024/07/04:[SenseVoice](https://github.com/FunAudioLLM/SenseVoice) is a speech foundation model with multiple speech understanding capabilities, including ASR, LID, SER, and AED.
- 2024/07/01: Offline File Transcription Service GPU 1.1 released, optimize BladeDISC model compatibility issues; ref to ([docs](runtime/readme.md))
- 2024/06/27: Offline File Transcription Service GPU 1.0 released, supporting dynamic batch processing and multi-threading concurrency. In the long audio test set, the single-thread RTF is 0.0076, and multi-threads' speedup is 1200+ (compared to 330+ on CPU); ref to ([docs](runtime/readme.md))
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|                            conformer-en <br> ( [⭐](https://modelscope.cn/models/damo/speech_conformer_asr-en-16k-vocab4199-pytorch/summary) [🤗](https://huggingface.co/funasr/conformer-en) )                             |                        speech recognition, non-streaming                         |       50000 hours, English       |    220M    |
|                               ct-punc <br> ( [⭐](https://modelscope.cn/models/damo/punc_ct-transformer_cn-en-common-vocab471067-large/summary) [🤗](https://huggingface.co/funasr/ct-punc) )                               |                             punctuation restoration                              |    100M, Mandarin and English    |    290M    | 
|                                   fsmn-vad <br> ( [⭐](https://modelscope.cn/models/damo/speech_fsmn_vad_zh-cn-16k-common-pytorch/summary) [🤗](https://huggingface.co/funasr/fsmn-vad) )                                   |                             voice activity detection                             | 5000 hours, Mandarin and English |    0.4M    | 
|                            fsmn-kws <br> ( [⭐](https://modelscope.cn/models/iic/speech_charctc_kws_phone-xiaoyun/summary) )                             |     keyword spotting,streaming      |  5000 hours, Mandarin  |  0.7M  |
|                                     fa-zh <br> ( [⭐](https://modelscope.cn/models/damo/speech_timestamp_prediction-v1-16k-offline/summary) [🤗](https://huggingface.co/funasr/fa-zh) )                                     |                               timestamp prediction                               |       5000 hours, Mandarin       |    38M     | 
|                                       cam++ <br> ( [⭐](https://modelscope.cn/models/iic/speech_campplus_sv_zh-cn_16k-common/summary) [🤗](https://huggingface.co/funasr/campplus) )                                        |                         speaker verification/diarization                         |            5000 hours            |    7.2M    | 
|                                 Whisper-large-v2 <br> ([⭐](https://www.modelscope.cn/models/iic/speech_whisper-large_asr_multilingual/summary)  [🍀](https://github.com/openai/whisper) )                                  |                speech recognition, with timestamps, non-streaming                |           multilingual           |   1550 M   |
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- `use_itn`: Whether the output result includes punctuation and inverse text normalization.
- `batch_size_s`: Indicates the use of dynamic batching, where the total duration of audio in the batch is measured in seconds (s).
- `merge_vad`: Whether to merge short audio fragments segmented by the VAD model, with the merged length being `merge_length_s`, in seconds (s).
- `ban_emo_unk`: Whether to ban the output of the `emo_unk` token.
#### Paraformer
```python
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## Community Communication
If you encounter problems in use, you can directly raise Issues on the github page.
You can also scan the following DingTalk group or WeChat group QR code to join the community group for communication and discussion.
You can also scan the following DingTalk group to join the community group for communication and discussion.
|                           DingTalk group                            |                     WeChat group                      |
|:-------------------------------------------------------------------:|:-----------------------------------------------------:|
| <div align="left"><img src="docs/images/dingding.png" width="250"/> | <img src="docs/images/wechat.png" width="215"/></div> |
|                           DingTalk group                            |
|:-------------------------------------------------------------------:|
| <div align="left"><img src="docs/images/dingding.png" width="250"/> |
## Contributors