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## Overview
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This bandwidth extension model
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The model is designed to to enhance the audio quality of body-conducted captured speech, by denoising and regenerating mid and high frequencies from low frequency content only.
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## Disclaimer
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This model
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Please be advised that using these models outside their intended sensor data may result in suboptimal performance.
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## Training procedure
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enhanced_audio_16kHz = model(cut_audio_16kHz)
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## Link to BWE models trained on other body conducted sensors :
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The entry point to all EBEN models for Bandwidth Extension (BWE) is available at [https://huggingface.co/Cnam-LMSSC/vibravox_EBEN_models](https://huggingface.co/Cnam-LMSSC/vibravox_EBEN_models).
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## Overview
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This bandwidth extension model, trained on [Vibravox](https://huggingface.co/datasets/Cnam-LMSSC/vibravox) body conduction sensor data, enhances body-conducted speech audio by denoising and regenerating mid and high frequencies from low-frequency content.
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## Disclaimer
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This model, trained for **a specific non-conventional speech sensor**, is intended to be used with **in-domain data**. Using it with other sensor data may lead to suboptimal performance.
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## Link to BWE models trained on other body conducted sensors :
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The entry point to all EBEN models for Bandwidth Extension (BWE) is available at [https://huggingface.co/Cnam-LMSSC/vibravox_EBEN_models](https://huggingface.co/Cnam-LMSSC/vibravox_EBEN_models).
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## Training procedure
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enhanced_audio_16kHz = model(cut_audio_16kHz)
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```
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