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| | | <a name="whats-new"></a> |
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| | | ## What's new: |
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| | | - 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. |
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| | | - 2024/07/01: Offline File Transcription Service GPU 1.1 released, optimize BladeDISC model compatibility issues; ref to ([docs](runtime/readme.md)) |
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| | | - 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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| | | - 2024/05/15：emotion recognition models are new supported. [emotion2vec+large](https://modelscope.cn/models/iic/emotion2vec_plus_large/summary)，[emotion2vec+base](https://modelscope.cn/models/iic/emotion2vec_plus_base/summary)，[emotion2vec+seed](https://modelscope.cn/models/iic/emotion2vec_plus_seed/summary). currently supports the following categories: 0: angry 1: happy 2: neutral 3: sad 4: unknown. |
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| | | - 2024/05/15: Offline File Transcription Service 4.5, Offline File Transcription Service of English 1.6，Real-time Transcription Service 1.10 released，adapting to FunASR 1.0 model structure；([docs](runtime/readme.md)) |
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| | | - 2024/03/05：Added the Qwen-Audio and Qwen-Audio-Chat large-scale audio-text multimodal models, which have topped multiple audio domain leaderboards. These models support speech dialogue, [usage](examples/industrial_data_pretraining/qwen_audio). |
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| | | (Note: ⭐ represents the ModelScope model zoo, 🤗 represents the Huggingface model zoo, 🍀 represents the OpenAI model zoo) |
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| | | | Model Name | Task Details | Training Data | Parameters | |
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| | | |:--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------:|:-----------------------------------------------------:|:--------------------------------:|:----------:| |
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| | | | paraformer-zh <br> ([⭐](https://www.modelscope.cn/models/damo/speech_paraformer-large-vad-punc_asr_nat-zh-cn-16k-common-vocab8404-pytorch/summary) [🤗](https://huggingface.co/funasr/paraformer-zh) ) | speech recognition, with timestamps, non-streaming | 60000 hours, Mandarin | 220M | |
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| | | | <nobr>paraformer-zh-streaming <br> ( [⭐](https://modelscope.cn/models/damo/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-online/summary) [🤗](https://huggingface.co/funasr/paraformer-zh-streaming) )</nobr> | speech recognition, streaming | 60000 hours, Mandarin | 220M | |
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| | | | paraformer-en <br> ( [⭐](https://www.modelscope.cn/models/damo/speech_paraformer-large-vad-punc_asr_nat-en-16k-common-vocab10020/summary) [🤗](https://huggingface.co/funasr/paraformer-en) ) | speech recognition, without timestamps, non-streaming | 50000 hours, English | 220M | |
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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 | |
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| | | | 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 | 1.1G | |
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| | | | 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 | |
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| | | | 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 | |
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| | | | 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 | |
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| | | | 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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| | | | Whisper-large-v3 <br> ([⭐](https://www.modelscope.cn/models/iic/Whisper-large-v3/summary) [🍀](https://github.com/openai/whisper) ) | speech recognition, with timestamps, non-streaming | multilingual | 1550 M | |
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| | | | Qwen-Audio <br> ([⭐](examples/industrial_data_pretraining/qwen_audio/demo.py) [🤗](https://huggingface.co/Qwen/Qwen-Audio) ) | audio-text multimodal models (pretraining) | multilingual | 8B | |
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| | | | Qwen-Audio-Chat <br> ([⭐](examples/industrial_data_pretraining/qwen_audio/demo_chat.py) [🤗](https://huggingface.co/Qwen/Qwen-Audio-Chat) ) | audio-text multimodal models (chat) | multilingual | 8B | |
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| | | | emotion2vec+large <br> ([⭐](https://modelscope.cn/models/iic/emotion2vec_plus_large/summary) [🤗](https://huggingface.co/emotion2vec/emotion2vec_plus_large) ) | speech emotion recongintion | 40000 hours | 300M | |
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| | | | Model Name | Task Details | Training Data | Parameters | |
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| | | |:--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------:|:--------------------------------------------------------------------------------:|:--------------------------------:|:----------:| |
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| | | | SenseVoiceSmall <br> ([⭐](https://www.modelscope.cn/models/iic/SenseVoiceSmall) [🤗](https://huggingface.co/FunAudioLLM/SenseVoiceSmall) ) | multiple speech understanding capabilities, including ASR, ITN, LID, SER, and AED, support languages such as zh, yue, en, ja, ko | 300000 hours | 234M | |
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| | | | paraformer-zh <br> ([⭐](https://www.modelscope.cn/models/damo/speech_paraformer-large-vad-punc_asr_nat-zh-cn-16k-common-vocab8404-pytorch/summary) [🤗](https://huggingface.co/funasr/paraformer-zh) ) | speech recognition, with timestamps, non-streaming | 60000 hours, Mandarin | 220M | |
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| | | | <nobr>paraformer-zh-streaming <br> ( [⭐](https://modelscope.cn/models/damo/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-online/summary) [🤗](https://huggingface.co/funasr/paraformer-zh-streaming) )</nobr> | speech recognition, streaming | 60000 hours, Mandarin | 220M | |
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| | | | paraformer-en <br> ( [⭐](https://www.modelscope.cn/models/damo/speech_paraformer-large-vad-punc_asr_nat-en-16k-common-vocab10020/summary) [🤗](https://huggingface.co/funasr/paraformer-en) ) | speech recognition, without timestamps, non-streaming | 50000 hours, English | 220M | |
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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 | |
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| | | | 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 | |
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| | | | 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 | |
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| | | | 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 | |
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| | | | 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 | |
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| | | | 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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| | | | Whisper-large-v3 <br> ([⭐](https://www.modelscope.cn/models/iic/Whisper-large-v3/summary) [🍀](https://github.com/openai/whisper) ) | speech recognition, with timestamps, non-streaming | multilingual | 1550 M | |
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| | | | Qwen-Audio <br> ([⭐](examples/industrial_data_pretraining/qwen_audio/demo.py) [🤗](https://huggingface.co/Qwen/Qwen-Audio) ) | audio-text multimodal models (pretraining) | multilingual | 8B | |
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| | | | Qwen-Audio-Chat <br> ([⭐](examples/industrial_data_pretraining/qwen_audio/demo_chat.py) [🤗](https://huggingface.co/Qwen/Qwen-Audio-Chat) ) | audio-text multimodal models (chat) | multilingual | 8B | |
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| | | | emotion2vec+large <br> ([⭐](https://modelscope.cn/models/iic/emotion2vec_plus_large/summary) [🤗](https://huggingface.co/emotion2vec/emotion2vec_plus_large) ) | speech emotion recongintion | 40000 hours | 300M | |
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| | | Notes: Support recognition of single audio file, as well as file list in Kaldi-style wav.scp format: `wav_id wav_pat` |
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| | | ### Speech Recognition (Non-streaming) |
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| | | #### SenseVoice |
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| | | ```python |
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| | | from funasr import AutoModel |
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| | | from funasr.utils.postprocess_utils import rich_transcription_postprocess |
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| | | model_dir = "iic/SenseVoiceSmall" |
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| | | model = AutoModel( |
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| | | model=model_dir, |
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| | | vad_model="fsmn-vad", |
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| | | vad_kwargs={"max_single_segment_time": 30000}, |
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| | | device="cuda:0", |
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| | | ) |
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| | | |
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| | | # en |
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| | | res = model.generate( |
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| | | input=f"{model.model_path}/example/en.mp3", |
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| | | cache={}, |
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| | | language="auto", # "zn", "en", "yue", "ja", "ko", "nospeech" |
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| | | use_itn=True, |
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| | | batch_size_s=60, |
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| | | merge_vad=True, # |
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| | | merge_length_s=15, |
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| | | ) |
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| | | text = rich_transcription_postprocess(res[0]["text"]) |
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| | | print(text) |
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| | | ``` |
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| | | Parameter Descriptions: |
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| | | - `model_dir`: The name of the model, or the model's path on the local disk. |
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| | | - `trust_remote_code`: |
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| | | - When set to `True`, this indicates that the model's code implementation should be loaded from the location specified by `remote_code`, which points to the exact code for the model (for example, `model.py` in the current directory). It supports absolute paths, relative paths, and network URLs. |
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| | | - When set to `False`, this signifies that the model's code implementation is the integrated version within [FunASR](https://github.com/modelscope/FunASR). In this case, any modifications to `model.py` in the current directory will not take effect because the version loaded is the internal one from FunASR. For the model code, [click here to view](https://github.com/modelscope/FunASR/tree/main/funasr/models/sense_voice). |
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| | | - `max_single_segment_time`: The maximum length of audio segments that the `vad_model` can cut, measured in milliseconds (ms). |
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| | | - `use_itn`: Indicates whether the output should include punctuation and inverse text normalization. |
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| | | - `batch_size_s`: Represents a dynamic batch size where the total duration of the audio in the batch is measured in seconds (s). |
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| | | - `merge_vad`: Whether to concatenate short audio fragments cut by the vad model, with the merged length being `merge_length_s`, measured in seconds (s). |
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| | | |
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| | | #### Paraformer |
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| | | ```python |
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| | | from funasr import AutoModel |
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| | | # paraformer-zh is a multi-functional asr model |
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