Indonesian General Conversation Database
Project Overview:
Objective
In our groundbreaking project, “Indonesian General Conversation Database,” we aim to develop a comprehensive dataset to enhance AI’s understanding of everyday Indonesian conversations. Our vision is to bridge the gap between artificial intelligence and natural human communication, focusing on the nuances of the Indonesian language. This dataset is an invaluable asset for developing more intuitive and responsive AI systems that can interact seamlessly in Indonesian.
Scope
To build this diverse dataset, our team embarked on collecting and annotating a vast range of general conversations in Indonesian. These include everyday dialogues, informal chats, and discussions on various topics. Our goal is to capture the essence of authentic Indonesian conversations, ensuring our AI models can understand and process the language in its most natural form.
Sources
- Recorded Conversations: From urban and rural regions of Indonesia, ensuring a diverse linguistic representation.
- Online Platforms: Gathering informal dialogues from social media, forums, and chat applications.
- Public and Private Events: Including conversations from various social and cultural events across Indonesia.
Data Collection Metrics
- Total Conversations Collected: 30,000
- Recorded Conversations: 15,000
- Online Platform Dialogues: 10,000
- Event-Based Conversations: 5,000
Annotation Process
Stages
- Conversation Transcription: Transcribing the audio files to text, maintaining the authenticity of the spoken language.
- Contextual Annotation: Annotating each conversation with context tags, emotional tones, and conversational nuances.
Annotation Metrics
- Conversations Transcribed and Annotated: 30,000
- Contextual Annotations: 30,000
Quality Assurance
Stages
Annotation Verification: Rigorous quality checks by linguistic experts to ensure accuracy and contextual relevance.
Data Quality Control: Filtering out conversations that don’t meet our quality standards or relevance criteria.
Data Security: Complying with data privacy laws and ensuring the confidentiality of conversation sources.
QA Metrics
- Annotation Validation Cases: 3,000 (10% of total)
- Data Cleansing: Exclusion of irrelevant or subpar conversations
Conclusion
The “Indonesian General Conversation Database” is a pioneering resource, pushing the boundaries of AI’s capabilities in understanding and engaging in natural Indonesian conversations. This dataset, with its rich annotations and diverse conversational examples, is a leap forward in making AI more relatable and effective in real-world Indonesian contexts. It’s a vital tool for developing AI that doesn’t just ‘speak’ but ‘understands’ Indonesian, fostering advancements in AI communication and interaction.
Quality Data Creation
Guaranteed TAT
ISO 9001:2015, ISO/IEC 27001:2013 Certified
HIPAA Compliance
GDPR Compliance
Compliance and Security
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