Indonesian General Conversation Database

Project Overview:

Objective

In our groundbreaking project, ā€œIndonesian General Conversation Database,ā€ we aim to develop a comprehensive dataset to enhance AIā€™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.

Indonesian General Conversation Database
Indonesian General Conversation Database
Indonesian General Conversation Database
Indonesian General Conversation Database

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.
case study-post
Indonesian General Conversation Database
Indonesian General Conversation Database

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

  1. Conversation Transcription: Transcribing the audio files to text, maintaining the authenticity of the spoken language.
  2. 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
Indonesian General Conversation Database
Indonesian General Conversation Database
Indonesian General Conversation Database
Indonesian General Conversation Database

Quality Assurance

Stages

Annotation Verification:Ā Rigorous quality checks by linguistic experts to ensure accuracy and contextual relevance.
Data Quality Control:Ā Filtering out conversations that donā€™t meet our quality standards or relevance criteria.
Data Security:Ā 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 ā€œIndonesian General Conversation Databaseā€ is a pioneering resource, pushing the boundaries of AIā€™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. Itā€™s a vital tool for developing AI that doesnā€™t just ā€˜speakā€™ but ā€˜understandsā€™ Indonesian, fostering advancements in AI communication and interaction.

Technology

Quality Data Creation

Technology

Guaranteed TAT

Technology

ISO 9001:2015, ISO/IEC 27001:2013 Certified

Technology

HIPAA Compliance

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GDPR Compliance

Technology

Compliance and Security

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