Hinglish call-center Dataset

Project Overview:

Objective

The “Hinglish Call-Center Dataset” initiative is designed to enhance customer service experiences and improve automated response systems. This project focuses on creating a rich dataset, combining Hindi and English (Hinglish), primarily for training advanced AI models in customer service applications.

Scope

This venture encompasses the collection and annotation of bilingual call center interactions. The dataset includes a diverse range of Hinglish conversations, covering various customer service scenarios.

Hinglish call-center Dataset
Hinglish call-center Dataset
Hinglish call-center Dataset
Hinglish call-center Dataset

Sources

  • Call Center Recordings: Authentic conversations between customers and agents.
  • Scripted Dialogues: Custom scripts acted out by bilingual speakers to cover a wide range of scenarios.
  • User-Generated Content: Voluntary submissions of Hinglish interactions from the public.
case study-post
Hinglish call-center Dataset
Hinglish call-center Dataset

Data Collection Metrics

  • Total Conversations Recorded: 25,000
  • Call Center Recordings: 15,000
  • Scripted Dialogues: 7,000
  • User-Generated Content: 3,000

Annotation Process

Stages

  1. Language Segmentation: Annotating the switch between Hindi and English within each conversation.
  2. Context Tagging: Labeling the context and intent of the conversation.
  3. Emotion Recognition: Identifying and labeling emotional tones.

Annotation Metrics

  • Conversations with Language Labels: 25,000
  • Context Tagging Completed: 25,000
  • Emotionally Annotated Conversations: 25,000
Hinglish call-center Dataset
Hinglish call-center Dataset
Hinglish call-center Dataset
Hinglish call-center Dataset

Quality Assurance

Stages

Annotation Review: A team of bilingual experts reviews the annotations for accuracy.
Data Cleansing: Removing irrelevant or low-quality recordings to ensure dataset integrity.
Data Security and Privacy: Ensuring compliance with data protection laws and ethical guidelines.

QA Metrics

  • Reviewed Annotations: 2,500 (10% of total)
  • Data Cleansing Initiatives: Continuous assessment and removal of subpar data.

Conclusion

The “Hinglish Call-Center Dataset” is a groundbreaking resource pivotal for advancing AI in customer service. With meticulously annotated bilingual conversations, it offers a versatile tool for developing sophisticated AI models that can seamlessly navigate Hinglish interactions, thereby revolutionizing customer service automation and enhancing user experience in bilingual environments.

Technology

Quality Data Creation

Technology

Guaranteed TAT

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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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