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-YAML tags:
-- copy-paste the tags obtained with the tagging app: https://github.com/huggingface/datasets-tagging
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-# Dataset Card for Nexdata/Hangzhou_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/30?source=Huggingface
-- **Repository:**
-- **Paper:**
-- **Leaderboard:**
-- **Point of Contact:**
-
-### Dataset Summary
-
-The data were collected from 370 speakers, each with about 500 spoken sentences in Hangzhou dialect. Local people in Hangzhou participated in the recording and the accent was authentic. The recording content is colloquial and life-oriented, and reading is more natural and fluent. Hangzhou locals participate in QA and proofreading, and text transcription is more accurate. Equipped with mainstream Android and Apple phones.
-                           
-For more details, please refer to the link: https://www.nexdata.ai/datasets/30?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
-
-Hangzhou 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
-
-[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/Mandarin_Spontaneous_Speech_Data
+
+## Description
+3,881 hours - Mandarin Spontaneous Speech Data, the content covering multiple subjects. 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, etc.
+
+For more details, please refer to the link: https://www.nexdata.ai/datasets/1024?source=Huggingface
+
+# Specifications
+## Format
+16kHz, 16bit, wav, mono channel;
+## Content Category
+Interview; Sports; Variety; Course; Entertainment, Service, etc.
+## Annotation
+annotation for the transcription text, speaker identification, gender
+## Language
+Mandarin
+## Accuracy
+at a Sentence Accuracy Rate (SAR) of being no less than 95%
+## Application scenarios
+speech recognition, video caption generation and video content review
+
+# Licensing Information
+Commerical License