Introduction
This Odia Call Center Speech Dataset for the Real Estate industry is purpose-built to accelerate the development of speech recognition, spoken language understanding, and conversational AI systems tailored for Odia -speaking Real Estate customers. With over 40 hours of unscripted, real-world audio, this dataset captures authentic conversations between customers and real estate agents ideal for building robust ASR models.
Curated by FutureBeeAI, this dataset equips voice AI developers, real estate tech platforms, and NLP researchers with the data needed to create high-accuracy, production-ready models for property-focused use cases.
Speech Data
The dataset features 40 hours of dual-channel call center recordings between native Odia speakers. Captured in realistic real estate consultation and support contexts, these conversations span a wide array of property-related topics from inquiries to investment advice offering deep domain coverage for AI model development.
•Participant Diversity:
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Speakers:
80 native Odia speakers from our verified contributor community.
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Regions:
Representing different regions across Odisha to ensure accent and dialect variation.
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Participant Profile:
Balanced gender mix (60% male, 40% female) and age range from 18 to 70.
•Recording Details:
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Conversation Nature:
Naturally flowing, unscripted agent-customer discussions.
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Call Duration:
Average 5–15 minutes per call.
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Audio Format:
Stereo WAV, 16-bit, recorded at 8kHz and 16kHz.
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Recording Environment:
Captured in noise-free and echo-free conditions.
Topic Diversity
This speech corpus includes both inbound and outbound calls, featuring positive, neutral, and negative outcomes across a wide range of real estate scenarios.
•Inbound Calls:•Property Features & Amenities
•Investment Property Evaluation
•Ownership History & Legal Info, and more
•Outbound Calls:•New Listing Notifications
•Post-Purchase Follow-ups
•Property Recommendations
•Customer Satisfaction Surveys, and others
Such domain-rich variety ensures model generalization across common real estate support conversations.
Transcription
All recordings are accompanied by precise, manually verified transcriptions in JSON format.
•Transcription Includes:•Speaker-Segmented Dialogues
•Non-speech Tags (e.g., background noise, pauses)
•High transcription accuracy with word error rate below 5% via dual-layer human review.
These transcriptions streamline ASR and NLP development for Odia real estate voice applications.
Metadata
Detailed metadata accompanies each participant and conversation:
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Participant Metadata:
ID, age, gender, location, accent, and dialect.
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Conversation Metadata:
Topic, call type, sentiment, sample rate, and technical details.
This enables smart filtering, dialect-focused model training, and structured dataset exploration.
Usage and Applications
This dataset is ideal for voice AI and NLP systems built for the real estate sector:
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Automatic Speech Recognition (ASR):
Train high-accuracy speech-to-text models in Odia.
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Speech Analytics:
Extract insights on buyer interest, investment intent, and property preferences.
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Chatbots & Voice Assistants:
Develop smart real estate virtual agents.
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Sentiment Analysis:
Detect urgency, uncertainty, or interest in property-related calls.
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Generative AI:
Fine-tune Odia language models for summarizing or responding to property inquiries.
Secure and Ethical Collection
•Data collected via FutureBeeAI’s secure platform “Yugo” with strict ethical oversight.
•No personally identifiable information is included.
•Fully compliant with global data privacy standards and copyright-free.
Updates and Customization
We continuously enhance this dataset with new recordings and offer full customization:
•Customization Options:
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Environment:
Silent, noisy, or varied real-world conditions on request.
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Sample Rate:
Adjustable from 8kHz to 48kHz.
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Transcription:
Custom formats and QA guidelines available.
License
This Real Estate domain dataset is commercially licensed and ready for use in your Odia ASR, NLP, and voice AI workflows.