Indian English Call Center Speech Dataset for Real Estate

This Indian English speech dataset features real-world call center conversations from the Real Estate domain. With detailed metadata and accurate transcriptions, it’s designed to power ASR systems, voice AI, and conversational agents.

About this Off-the-shelf Speech Dataset

Introduction

This Indian English 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 English -speaking Real Estate customers. With over 30 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 30 hours of dual-channel call center recordings between native Indian English 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:

•

Speakers: 60 native Indian English speakers from our verified contributor community.

•

Regions: Representing different provinces across India to ensure accent and dialect variation.

•

Participant Profile: Balanced gender mix (60% male, 40% female) and age range from 18 to 70.

•Recording Details:

•

Conversation Nature: Naturally flowing, unscripted agent-customer discussions.

•

Call Duration: Average 5–15 minutes per call.

•

Audio Format: Stereo WAV, 16-bit, recorded at 8kHz and 16kHz.

•

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 Inquiries

•Rental Availability

•Renovation Consultation

•Property Features & Amenities

•Investment Property Evaluation

•Ownership History & Legal Info, and more

•Outbound Calls:

•New Listing Notifications

•Post-Purchase Follow-ups

•Property Recommendations

•Value Updates

•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

•Time-coded Segments

•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 English real estate voice applications.

Metadata

Detailed metadata accompanies each participant and conversation:

•

Participant Metadata: ID, age, gender, location, accent, and dialect.

•

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:

•

Automatic Speech Recognition (ASR): Train high-accuracy speech-to-text models in Indian English.

•

Speech Analytics: Extract insights on buyer interest, investment intent, and property preferences.

•

Chatbots & Voice Assistants: Develop smart real estate virtual agents.

•

Sentiment Analysis: Detect urgency, uncertainty, or interest in property-related calls.

•

Generative AI: Fine-tune English 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:

•

Environment: Silent, noisy, or varied real-world conditions on request.

•

Sample Rate: Adjustable from 8kHz to 48kHz.

•

Transcription: Custom formats and QA guidelines available.

License

This Real Estate domain dataset is commercially licensed and ready for use in your English ASR, NLP, and voice AI workflows.

Use Cases

Call Center Conversational AI

Use of speech data for Automatic Speech Recognition

ASR

Chatbot

Language Modelling

TTS

Speech Analytics

Dataset Sample(s)

Dataset Details

Language

English

Language code

en-In

Country

India

Accents

Chandigarh, Chhattisgarh ...moreDelhi, Gujarat, Jammu and Kashmir, Kerala, Madhya Pradesh, Maharashtra, Odisha, Rajasthan, Tamil Nadu, Telangana, Uttar Pradesh, Uttarakhand, West Bengal

Gender Distribution

M:60, F:40

Age Group

18-70 Years

File Details

Environment

Silent, Noisy

Bit Depth

16 bit

Format

wav

Sample rate

8khz & 16khz

Channel

Stereo (dual-channel, separated speakers)

Audio file duration

5-15 minutes

Read the License Terms

Browse FAQs

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Indian English Call Center Speech Dataset for Real Estate

About this Off-the-shelf Speech Dataset

Introduction

Speech Data

•Participant Diversity:

•

Speakers: 60 native Indian English speakers from our verified contributor community.

•

Regions: Representing different provinces across India to ensure accent and dialect variation.

•

Participant Profile: Balanced gender mix (60% male, 40% female) and age range from 18 to 70.

•Recording Details:

•

Conversation Nature: Naturally flowing, unscripted agent-customer discussions.

•

Call Duration: Average 5–15 minutes per call.

•

Audio Format: Stereo WAV, 16-bit, recorded at 8kHz and 16kHz.

•

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 Inquiries

•Rental Availability

•Renovation Consultation

•Property Features & Amenities

•Investment Property Evaluation

•Ownership History & Legal Info, and more

•Outbound Calls:

•New Listing Notifications

•Post-Purchase Follow-ups

•Property Recommendations

•Value Updates

•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

•Time-coded Segments

•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 English real estate voice applications.

Metadata

Detailed metadata accompanies each participant and conversation:

•

Participant Metadata: ID, age, gender, location, accent, and dialect.

•

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:

•

Automatic Speech Recognition (ASR): Train high-accuracy speech-to-text models in Indian English.

•

Speech Analytics: Extract insights on buyer interest, investment intent, and property preferences.

•

Chatbots & Voice Assistants: Develop smart real estate virtual agents.

•

Sentiment Analysis: Detect urgency, uncertainty, or interest in property-related calls.

•

Generative AI: Fine-tune English 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:

•

Environment: Silent, noisy, or varied real-world conditions on request.

•

Sample Rate: Adjustable from 8kHz to 48kHz.

•

Transcription: Custom formats and QA guidelines available.

License

This Real Estate domain dataset is commercially licensed and ready for use in your English ASR, NLP, and voice AI workflows.

Use Cases

Call Center Conversational AI

ASR

Chatbot

Language Modelling

TTS

Speech Analytics

Dataset Sample(s)

Dataset Details

Language

English

Language code

en-In

Country

India

Accents

Chandigarh, Chhattisgarh ...moreDelhi, Gujarat, Jammu and Kashmir, Kerala, Madhya Pradesh, Maharashtra, Odisha, Rajasthan, Tamil Nadu, Telangana, Uttar Pradesh, Uttarakhand, West Bengal

Gender Distribution

M:60, F:40

Age Group

18-70 Years