Our primary objective was to create a comprehensive audio dataset, the Korean Media Audio, that captures the nuances of spoken Korean, particularly in healthcare contexts. This dataset aims to enhance the accuracy and responsiveness of AI-driven applications in healthcare, from patient interaction systems to diagnostic and treatment recommendation engines.
Scope
Collection of over 10,000 hours of Korean audio content. Annotation of audio files with precise transcriptions, sentiment analysis, and contextual tagging. Quality assurance processes to ensure data accuracy and usability in AI applications.
Sources
Audio sources were meticulously chosen to cover a broad spectrum of spoken Korean:
News broadcasts covering health-related topics.
Medical podcasts and interviews with healthcare professionals.
Conversational dialogues in clinical and casual settings.
Transcription: Verbatim transcription of spoken content.
Sentiment Analysis: Categorization of clips according to emotional tone.
Contextual Tagging: Tagging clips with relevant healthcare topics and conversational contexts.
Annotation Metrics
Clips Annotated: 15,000
Average Annotation Time per Clip: 5 minutes
Total Annotation Hours: 1,250 hours
Quality Assurance
Stages
Accuracy of Transcription: 98%
Consistency in Sentiment Analysis: 95%
Correctness in Contextual Tagging: 97%
QA Metrics
Total Validation Cases: 5,000
Annotation Accuracy Validation: Success rate of 98% for transcription accuracy
Sentiment Analysis Consistency: 95% consistency across different reviewers
Conclusion
The “Korean Media Audio Dataset” stands as a testament to our commitment to high-quality data collection and annotation for AI development. With its diverse content, meticulous annotation, and stringent quality control, this dataset is an invaluable asset for anyone looking to build or enhance AI systems that interact with Korean media content.
Quality Data Creation
Guaranteed TAT
ISO 9001:2015, ISO/IEC 27001:2013 Certified
HIPAA Compliance
GDPR Compliance
Compliance and Security
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Requirement With Us
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