Chinese & English & Tibetan & Uyghur Language Dataset
Project Overview:
Objective
mission was to curate a comprehensive dataset encompassing Chinese, English, Tibetan, and Uyghur languages for machine learning model training. This multi-lingual dataset serves as a valuable resource for a wide range of applications, including natural language processing, sentiment analysis, and machine translation.
Scope
Our project involved the meticulous collection of Multi-Language Dataset data in Chinese, English, Tibetan, and Uyghur languages from diverse sources, followed by rigorous annotation to ensure data accuracy and usability.
Sources
- Web Crawling: We employed web crawling techniques to gather a vast amount of text data from websites, forums, and articles in the target languages.
- Public Datasets: Accessing publicly available text datasets allowed us to augment our collection with high-quality content.
- Collaboration: Collaborative efforts with linguists and native speakers aided in the acquisition of authentic and contextually relevant data.
Data Collection Metrics
- Total Text Data Collected: Over 1.5 million documents
- Chinese Texts: 600,000 documents
- English Texts: 500,000 documents
- Tibetan Texts: 200,000 documents
- Uyghur Texts: 200,000 documents
Annotation Process
Stages
- Language Labeling: Each document was meticulously annotated with its respective language label.
- Sentiment Analysis: We conducted sentiment analysis to provide insights into the emotional tone of the text.
- Topic Categorization: Documents were categorized into various topics to enhance the dataset’s usability.
Annotation Metrics
- Language Labels: 1.5 million documents
- Sentiment Analysis Scores: 1.2 million documents
- Topic Categories: 800,000 documents
Quality Assurance
Stages
Expert Review: We engaged linguists and native speakers to validate the accuracy of language labeling and sentiment analysis.
Data Cleansing: Rigorous quality control ensured the removal of irrelevant or low-quality texts.
Data Security: Stringent data security protocols were in place to protect sensitive linguistic content and user privacy.
QA Metrics
- Expert Validation Cases: 5,000 documents
- Data Cleansing: 10,000 documents
Conclusion
The “Chinese & English & Tibetan & Uyghur Language Dataset” represents a significant milestone in linguistic data curation. This diverse and extensive dataset serves as a valuable asset for the development of machine learning models and applications that require multilingual text analysis. Its accuracy, breadth, and depth make it an indispensable resource for researchers and developers in the field of natural language processing.
Quality Data Creation
Guaranteed TAT
ISO 9001:2015, ISO/IEC 27001:2013 Certified
HIPAA Compliance
GDPR Compliance
Compliance and Security
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