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Bahasa Call Center Data for Realestate AI
- futurebeeai.com
wavUpdated Aug 1, 2022
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EmailClick to copy linkLink copiedCiteFutureBee AI (2022). Bahasa Call Center Data for Realestate AI [Dataset]. https://www.futurebeeai.com/dataset/speech-dataset/realestate-call-center-conversation-bahasa-indonesiawavAvailable download formatsDataset updatedAug 1, 2022Dataset provided byFutureBeeAIAuthorsFutureBee AILicensehttps://www.futurebeeai.com/policies/ai-data-license-agreementhttps://www.futurebeeai.com/policies/ai-data-license-agreement
Dataset funded byFutureBeeAIDescriptionIntroduction
This Bahasa 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 Bahasa -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 Bahasa 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: 80 native Bahasa speakers from our verified contributor community.•Regions: Representing different provinces across Indonesia 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 othersSuch 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 Bahasa 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:
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Hindi Call Center Data for Realestate AI
- futurebeeai.com
wavUpdated Aug 1, 2022ShareFacebookTwitterEmailClick to copy linkLink copiedCiteFutureBee AI (2022). Hindi Call Center Data for Realestate AI [Dataset]. https://www.futurebeeai.com/dataset/speech-dataset/realestate-call-center-conversation-hindi-indiawavAvailable download formatsDataset updatedAug 1, 2022Dataset provided byFutureBeeAIAuthorsFutureBee AILicensehttps://www.futurebeeai.com/policies/ai-data-license-agreementhttps://www.futurebeeai.com/policies/ai-data-license-agreement
Dataset funded byFutureBeeAIDescriptionIntroduction
This Hindi 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 Hindi -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 Hindi 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 Hindi 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 othersSuch 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 Hindi 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:
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American English Call Center Data for Realestate AI
- futurebeeai.com
wavUpdated Aug 1, 2022ShareFacebookTwitterEmailClick to copy linkLink copiedCiteFutureBee AI (2022). American English Call Center Data for Realestate AI [Dataset]. https://www.futurebeeai.com/dataset/speech-dataset/realestate-call-center-conversation-english-usawavAvailable download formatsDataset updatedAug 1, 2022Dataset provided byFutureBeeAIAuthorsFutureBee AILicensehttps://www.futurebeeai.com/policies/ai-data-license-agreementhttps://www.futurebeeai.com/policies/ai-data-license-agreement
Area coveredUnited StatesDataset funded byFutureBeeAIDescriptionIntroduction
This US 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 US 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 US English speakers from our verified contributor community.•Regions: Representing different provinces across United States of America 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 othersSuch 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:
<div style="margin-top:10px; margin-bottom: 10px; padding-left: 30px; display: flex; gap: 16px; - F
Canadian English Call Center Data for Realestate AI
- futurebeeai.com
wavUpdated Aug 1, 2022ShareFacebookTwitterEmailClick to copy linkLink copiedCiteFutureBee AI (2022). Canadian English Call Center Data for Realestate AI [Dataset]. https://www.futurebeeai.com/dataset/speech-dataset/realestate-call-center-conversation-english-canadawavAvailable download formatsDataset updatedAug 1, 2022Dataset provided byFutureBeeAIAuthorsFutureBee AILicensehttps://www.futurebeeai.com/policies/ai-data-license-agreementhttps://www.futurebeeai.com/policies/ai-data-license-agreement
Area coveredCanadaDataset funded byFutureBeeAIDescriptionIntroduction
This Canadian 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 Canadian 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 Canadian English speakers from our verified contributor community.•Regions: Representing different provinces across Canada 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 othersSuch 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:
<div style="margin-top:10px; margin-bottom: 10px; padding-left: 30px; display: flex; gap: 16px; - F
British English Call Center Data for Realestate AI
- futurebeeai.com
wavUpdated Aug 1, 2022ShareFacebookTwitterEmailClick to copy linkLink copiedCiteFutureBee AI (2022). British English Call Center Data for Realestate AI [Dataset]. https://www.futurebeeai.com/dataset/speech-dataset/realestate-call-center-conversation-english-ukwavAvailable download formatsDataset updatedAug 1, 2022Dataset provided byFutureBeeAIAuthorsFutureBee AILicensehttps://www.futurebeeai.com/policies/ai-data-license-agreementhttps://www.futurebeeai.com/policies/ai-data-license-agreement
Dataset funded byFutureBeeAIDescriptionIntroduction
This UK 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 UK 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 UK English speakers from our verified contributor community.•Regions: Representing different provinces across United Kingdom 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 othersSuch 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:
<div style="margin-top:10px; margin-bottom: 10px; padding-left: 30px; display: flex; gap: 16px; align-items: - F
Indian English Call Center Data for Realestate AI
- futurebeeai.com
wavUpdated Aug 1, 2022ShareFacebookTwitterEmailClick to copy linkLink copiedCiteFutureBee AI (2022). Indian English Call Center Data for Realestate AI [Dataset]. https://www.futurebeeai.com/dataset/speech-dataset/realestate-call-center-conversation-english-indiawavAvailable download formatsDataset updatedAug 1, 2022Dataset provided byFutureBeeAIAuthorsFutureBee AILicensehttps://www.futurebeeai.com/policies/ai-data-license-agreementhttps://www.futurebeeai.com/policies/ai-data-license-agreement
Dataset funded byFutureBeeAIDescriptionIntroduction
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 othersSuch 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:
<div style="margin-top:10px; margin-bottom: 10px; padding-left: 30px; display: flex; gap: 16px; align-items: 
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Bahasa call center speech corpus in realestate industry
https://www.futurebeeai.com/policies/ai-data-license-agreementhttps://www.futurebeeai.com/policies/ai-data-license-agreement
Introduction
This Bahasa 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 Bahasa -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 Bahasa 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.
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.
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.
These transcriptions streamline ASR and NLP development for Bahasa real estate voice applications.
Metadata
Detailed metadata accompanies each participant and conversation:
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: