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@@ -25,20 +25,20 @@ We host several models, which are specifically tailored to the processing of Fle
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  ### Automatic Speech Recognition (ASR)
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- -- **NeLF_S2T_Pytorch** (Recommended): The third version of our Automatic Speech Recognition and Subtitle Generation model. It is a fine-tuned version of ASR_subtitles_v2 without Kaldi-dependency (pure Pytorch), and refined training data leveraging contextualisation techniques for pseudo-labeling.
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- -- **ASR_subtitles_v2**: The second version of our Automatic Speech Recognition and Subtitle Generation model, with improved architecture and trained on 14000 hours of Flemish broadcast subtitled speech data.
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  It can generate both an exact verbatim transcription with annotation tags as well as a fully formatted and cleaned up subtitle transcription.
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- -- **ASR_subtitles_v2_small**: Smaller variant of ASR_subtitles_v2 with almost as good performance.
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- -- **ASR_subtitles_v1**: The first version of the ASR and Subtitling model trained on 1000 hours of Flemish data.
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- -- **ASR_verbatim_v1**: The first version of the ASR and Subtitling model trained on 1000 hours of Flemish data, converted to a verbatim-only ASR model.
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  -- **Whisper**: A finetuned Whisper Large model on Flemish data can be found [here](https://huggingface.co/kul-speech-lab/whisper_large_CGN). Usage instructions can be found in Whisper documentation.
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- **USAGE**: To use our ASR models and transcribe speech yourself, use [our codebase](https://github.com/nelfproject/NeLF_Transcription_ASR).
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  ### Speaker Diarization and Identification
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  ### Automatic Speech Recognition (ASR)
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+ -- [**NeLF_S2T_Pytorch**](https://huggingface.co/nelfproject/NeLF_S2T_Pytorch) (Recommended): The third version of our Automatic Speech Recognition and Subtitle Generation model. It is a fine-tuned version of ASR_subtitles_v2 without Kaldi-dependency (pure Pytorch), and refined training data leveraging contextualisation techniques for pseudo-labeling.
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+ -- [**ASR_subtitles_v2**](https://huggingface.co/nelfproject/ASR_subtitles_v2): The second version of our Automatic Speech Recognition and Subtitle Generation model, with improved architecture and trained on 14000 hours of Flemish broadcast subtitled speech data.
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  It can generate both an exact verbatim transcription with annotation tags as well as a fully formatted and cleaned up subtitle transcription.
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+ -- [**ASR_subtitles_v2_small**](https://huggingface.co/nelfproject/ASR_subtitles_v2_small): Smaller variant of ASR_subtitles_v2 with almost as good performance.
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+ -- [**ASR_subtitles_v1**](https://huggingface.co/nelfproject/ASR_subtitles_v1): The first version of the ASR and Subtitling model trained on 1000 hours of Flemish data.
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+ -- [**ASR_verbatim_v1**](https://huggingface.co/nelfproject/ASR_verbatim_v1): The first version of the ASR and Subtitling model trained on 1000 hours of Flemish data, converted to a verbatim-only ASR model.
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  -- **Whisper**: A finetuned Whisper Large model on Flemish data can be found [here](https://huggingface.co/kul-speech-lab/whisper_large_CGN). Usage instructions can be found in Whisper documentation.
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+ **USAGE**: To use our ASR models and transcribe speech yourself, use [our Github](https://github.com/nelfproject/NeLF_Speech2Text_Pytorch) for NeLF_S2T_Pytorch or [our codebase](https://github.com/nelfproject/NeLF_Transcription_ASR) for previous versions.
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  ### Speaker Diarization and Identification
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