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README.md
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- DiCoW
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- BUT-FIT
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pipeline_tag: automatic-speech-recognition
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license:
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datasets:
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- microsoft/NOTSOFAR
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- edinburghcstr/ami
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This repository contains the **DiCoW\_v3\_MLC** model developed by [BUT Speech@FIT](https://github.com/BUTSpeechFIT) for the [MLC-SLM Challenge](https://www.nexdata.ai/competition/mlc-slm).
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Diarization-Conditioned Whisper (DiCoW) is a novel approach to target-speaker ASR that leverages speaker diarization outputs as conditioning information.
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The model is described in detail in the following papers:
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* 📰 **Journal paper (main DiCoW paper):** [DiCoW: Diarization-Conditioned Whisper for Target Speaker Automatic Speech Recognition](https://authors.elsevier.com/a/1lI9m_K8BYumVY)
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- DiCoW
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- BUT-FIT
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pipeline_tag: automatic-speech-recognition
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license: cc-by-4.0
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datasets:
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- microsoft/NOTSOFAR
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- edinburghcstr/ami
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This repository contains the **DiCoW\_v3\_MLC** model developed by [BUT Speech@FIT](https://github.com/BUTSpeechFIT) for the [MLC-SLM Challenge](https://www.nexdata.ai/competition/mlc-slm).
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Diarization-Conditioned Whisper (DiCoW) is a novel approach to target-speaker ASR that leverages speaker diarization outputs as conditioning information.
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This model is available under the terms of CC BY 4.0. It incorporates an MIT-licensed base model and CC BY 4.0 licensed training data.
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The model is described in detail in the following papers:
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* 📰 **Journal paper (main DiCoW paper):** [DiCoW: Diarization-Conditioned Whisper for Target Speaker Automatic Speech Recognition](https://authors.elsevier.com/a/1lI9m_K8BYumVY)
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