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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/Wuhan_Dialect_Speech_Data_by_Mobile_Phone
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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/3bbSVdT
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  - **Repository:**
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  - **Paper:**
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  - **Leaderboard:**
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  Mobile phone captured audio data of Wuhan dialect, 997 hours in total, recorded by more than 2,000 Wuhan dialect native speakers. The recorded text covers generic, interactive, on-board, home and other categories, with rich contents. Wuhan locals participate in quality check and proofreading. Sentence accuracy rate reaches 95 %; this data set can be used for automatic speech recognition, machine translation, and voiceprint recognition.
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- For more details, please refer to the link: https://bit.ly/3bbSVdT
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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/Wuhan_Dialect_Speech_Data_by_Mobile_Phone
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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/942?source=Huggingface
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  - **Repository:**
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  - **Paper:**
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  - **Leaderboard:**
 
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  Mobile phone captured audio data of Wuhan dialect, 997 hours in total, recorded by more than 2,000 Wuhan dialect native speakers. The recorded text covers generic, interactive, on-board, home and other categories, with rich contents. Wuhan locals participate in quality check and proofreading. Sentence accuracy rate reaches 95 %; this data set can be used for automatic speech recognition, machine translation, and voiceprint recognition.
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+ For more details, please refer to the link: https://www.nexdata.ai/datasets/942?source=Huggingface
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  ### Supported Tasks and Leaderboards
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