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-- copy-paste the tags obtained with the tagging app: https://github.com/huggingface/datasets-tagging
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-# Dataset Card for Nexdata/Wuhan_Dialect_Speech_Data_by_Mobile_Phone
-
-## Table of Contents
-- [Table of Contents](#table-of-contents)
-- [Dataset Description](#dataset-description)
-  - [Dataset Summary](#dataset-summary)
-  - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
-  - [Languages](#languages)
-- [Dataset Structure](#dataset-structure)
-  - [Data Instances](#data-instances)
-  - [Data Fields](#data-fields)
-  - [Data Splits](#data-splits)
-- [Dataset Creation](#dataset-creation)
-  - [Curation Rationale](#curation-rationale)
-  - [Source Data](#source-data)
-  - [Annotations](#annotations)
-  - [Personal and Sensitive Information](#personal-and-sensitive-information)
-- [Considerations for Using the Data](#considerations-for-using-the-data)
-  - [Social Impact of Dataset](#social-impact-of-dataset)
-  - [Discussion of Biases](#discussion-of-biases)
-  - [Other Known Limitations](#other-known-limitations)
-- [Additional Information](#additional-information)
-  - [Dataset Curators](#dataset-curators)
-  - [Licensing Information](#licensing-information)
-  - [Citation Information](#citation-information)
-  - [Contributions](#contributions)
-
-## Dataset Description
-
-- **Homepage:** https://www.nexdata.ai/datasets/942?source=Huggingface
-- **Repository:**
-- **Paper:**
-- **Leaderboard:**
-- **Point of Contact:**
-
-### Dataset Summary
-
-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.
-                           
-For more details, please refer to the link: https://www.nexdata.ai/datasets/942?source=Huggingface
-
-### Supported Tasks and Leaderboards
-
-automatic-speech-recognition, audio-speaker-identification: The dataset can be used to train a model for Automatic Speech Recognition (ASR).
-
-### Languages
-
-Wuhan Dialect
-## Dataset Structure
-
-### Data Instances
-
-[More Information Needed]
-
-### Data Fields
-
-[More Information Needed]
-
-### Data Splits
-
-[More Information Needed]
-
-## Dataset Creation
-
-### Curation Rationale
-
-[More Information Needed]
-
-### Source Data
-
-#### Initial Data Collection and Normalization
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-[More Information Needed]
-
-#### Who are the source language producers?
-
-[More Information Needed]
-
-### Annotations
-
-#### Annotation process
-
-[More Information Needed]
-
-#### Who are the annotators?
-
-[More Information Needed]
-
-### Personal and Sensitive Information
-
-[More Information Needed]
-
-## Considerations for Using the Data
-
-### Social Impact of Dataset
-
-[More Information Needed]
-
-### Discussion of Biases
-
-[More Information Needed]
-
-### Other Known Limitations
-
-[More Information Needed]
-
-## Additional Information
-
-### Dataset Curators
-
-[More Information Needed]
-
-### Licensing Information
-
-Commerical License: https://drive.google.com/file/d/1saDCPm74D4UWfBL17VbkTsZLGfpOQj1J/view?usp=sharing  
-
-### Citation Information
-
-[More Information Needed]
-
-### Contributions
-
+# Dataset Card for Nexdata/UAE_Arabic_Spontaneous_Speech_Data
+
+## Description
+The 749 hour UAE Arabic Spontaneous Speech Data, the content covering multiple topics. All the speech audio was manually transcribed into text content; speaker identity, gender, and other attribution are also annotated. This dataset can be used for voiceprint recognition model training, corpus construction for machine translation, and algorithm research introduction
+
+For more details, please refer to the link: https://www.nexdata.ai/datasets/1180?source=Huggingface
+
+# Specifications
+## Format
+16kHz, 16bit, mono channel;
+## Content category
+Interview; Speech; Variety, etc.
+## Language
+UAE Arabic;
+## Annotation
+annotation for the transcription text, speaker identification, gender;
+## Application scenarios
+speech recognition, video caption generation and video content review;
+## Accuracy
+at a Sentence Accuracy Rate (SAR) of being no less than 95%.
+
+# Licensing Information
+Commerical License