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  - copy-paste the tags obtained with the tagging app: https://github.com/huggingface/datasets-tagging
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  ---
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- # Dataset Card for Datatang/Scene_Noise_Data_by_Voice_Recorder
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  ## Table of Contents
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  - [Table of Contents](#table-of-contents)
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  ## Dataset Description
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- - **Homepage:** https://bit.ly/3zYDIY3
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  - **Repository:**
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  - **Paper:**
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  - **Leaderboard:**
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  The data is multi-scene noise data, covering subway, supermarket, restaurant, road, airport, exhibition hall, high-speed rail, highway, city road, cinema and other daily life scenes.The data is recorded by the professional recorder Sony ICD-UX560F, which is collected in a high sampling rate and two-channel format, and the recording is clear and natural. The valid data is 101 hours.
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- For more details, please refer to the link: https://bit.ly/3zYDIY3
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  ### Supported Tasks and Leaderboards
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  - copy-paste the tags obtained with the tagging app: https://github.com/huggingface/datasets-tagging
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  ---
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+ # Dataset Card for Nexdata/Scene_Noise_Data_by_Voice_Recorder
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  ## Table of Contents
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  - [Table of Contents](#table-of-contents)
 
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  ## Dataset Description
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+ - **Homepage:** https://www.nexdata.ai/datasets/25?source=Huggingface
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  - **Repository:**
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  - **Paper:**
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  - **Leaderboard:**
 
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  The data is multi-scene noise data, covering subway, supermarket, restaurant, road, airport, exhibition hall, high-speed rail, highway, city road, cinema and other daily life scenes.The data is recorded by the professional recorder Sony ICD-UX560F, which is collected in a high sampling rate and two-channel format, and the recording is clear and natural. The valid data is 101 hours.
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+ For more details, please refer to the link: https://www.nexdata.ai/datasets/25?source=Huggingface
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  ### Supported Tasks and Leaderboards
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