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Bahasa Call Center Data for Travel AI
- futurebeeai.com
wavUpdated Aug 1, 2022
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EmailClick to copy linkLink copiedCiteFutureBee AI (2022). Bahasa Call Center Data for Travel AI [Dataset]. https://www.futurebeeai.com/dataset/speech-dataset/travel-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 Travel industry is purpose-built to power the next generation of voice AI applications for travel booking, customer support, and itinerary assistance. With over 40 hours of unscripted, real-world conversations, the dataset enables the development of highly accurate speech recognition and natural language understanding models tailored for Bahasa -speaking travelers.
Created by FutureBeeAI, this dataset supports researchers, data scientists, and conversational AI teams in building voice technologies for airlines, travel portals, and hospitality platforms.
Speech Data
The dataset includes 40 hours of dual-channel audio recordings between native Bahasa speakers engaged in real travel-related customer service conversations. These audio files reflect a wide variety of topics, accents, and scenarios found across the travel and tourism industry.
•Participant Diversity:•Speakers: 80 native Bahasa contributors from our verified pool.•Regions: Covering multiple Indonesia provinces to capture accent and dialectal variation.•Participant Profile: Balanced representation of age (18–70) and gender (60% male, 40% female).•Recording Details:•Conversation Nature: Naturally flowing, spontaneous customer-agent calls.•Call Duration: Between 5 and 15 minutes per session.•Audio Format: Stereo WAV, 16-bit depth, at 8kHz and 16kHz.•Recording Environment: Captured in controlled, noise-free, echo-free settings.Topic Diversity
Inbound and outbound conversations span a wide range of real-world travel support situations with varied outcomes (positive, neutral, negative).
•Inbound Calls:•Booking Assistance•Destination Information•Flight Delays or Cancellations•Support for Disabled Passengers•Health and Safety Travel Inquiries•Lost or Delayed Luggage, and more•Outbound Calls:•Promotional Travel Offers•Customer Feedback Surveys•Booking Confirmations•Flight Rescheduling Alerts•Visa Expiry Notifications, and othersThese scenarios help models understand and respond to diverse traveler needs in real-time.
Transcription
Each call is accompanied by manually curated, high-accuracy transcriptions in JSON format.
•Transcription Includes:•Speaker-Segmented Dialogues•Time-Stamped Segments•Non-speech Markers (e.g., pauses, coughs)•High transcription accuracy by dual-layered transcription review ensures word error rate under 5%.Metadata
Extensive metadata enriches each call and speaker for better filtering and AI training:
•Participant Metadata: ID, age, gender, region, accent, and dialect.•Conversation Metadata: Topic, domain, call type, sentiment, and audio specs.Usage and Applications
This dataset is ideal for a variety of AI use cases in the travel and tourism space:
•ASR Systems: Train Bahasa speech-to-text engines for travel platforms.<div style="margin-top:10px; margin-bottom: 10px; padding-left: 30px; display: flex; - F
Urdu Call Center Data for Travel AI
- futurebeeai.com
wavUpdated Aug 1, 2022ShareFacebookTwitterEmailClick to copy linkLink copiedCiteFutureBee AI (2022). Urdu Call Center Data for Travel AI [Dataset]. https://www.futurebeeai.com/dataset/speech-dataset/travel-call-center-conversation-urdu-pakistanwavAvailable 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 Urdu Call Center Speech Dataset for the Travel industry is purpose-built to power the next generation of voice AI applications for travel booking, customer support, and itinerary assistance. With over 30 hours of unscripted, real-world conversations, the dataset enables the development of highly accurate speech recognition and natural language understanding models tailored for Urdu -speaking travelers.
Created by FutureBeeAI, this dataset supports researchers, data scientists, and conversational AI teams in building voice technologies for airlines, travel portals, and hospitality platforms.
Speech Data
The dataset includes 30 hours of dual-channel audio recordings between native Urdu speakers engaged in real travel-related customer service conversations. These audio files reflect a wide variety of topics, accents, and scenarios found across the travel and tourism industry.
•Participant Diversity:•Speakers: 60 native Urdu contributors from our verified pool.•Regions: Covering multiple Pakistan provinces to capture accent and dialectal variation.•Participant Profile: Balanced representation of age (18–70) and gender (60% male, 40% female).•Recording Details:•Conversation Nature: Naturally flowing, spontaneous customer-agent calls.•Call Duration: Between 5 and 15 minutes per session.•Audio Format: Stereo WAV, 16-bit depth, at 8kHz and 16kHz.•Recording Environment: Captured in controlled, noise-free, echo-free settings.Topic Diversity
Inbound and outbound conversations span a wide range of real-world travel support situations with varied outcomes (positive, neutral, negative).
•Inbound Calls:•Booking Assistance•Destination Information•Flight Delays or Cancellations•Support for Disabled Passengers•Health and Safety Travel Inquiries•Lost or Delayed Luggage, and more•Outbound Calls:•Promotional Travel Offers•Customer Feedback Surveys•Booking Confirmations•Flight Rescheduling Alerts•Visa Expiry Notifications, and othersThese scenarios help models understand and respond to diverse traveler needs in real-time.
Transcription
Each call is accompanied by manually curated, high-accuracy transcriptions in JSON format.
•Transcription Includes:•Speaker-Segmented Dialogues•Time-Stamped Segments•Non-speech Markers (e.g., pauses, coughs)•High transcription accuracy by dual-layered transcription review ensures word error rate under 5%.Metadata
Extensive metadata enriches each call and speaker for better filtering and AI training:
•Participant Metadata: ID, age, gender, region, accent, and dialect.•Conversation Metadata: Topic, domain, call type, sentiment, and audio specs.Usage and Applications
This dataset is ideal for a variety of AI use cases in the travel and tourism space:
•ASR Systems: Train Urdu speech-to-text engines for travel platforms.<div style="margin-top:10px; margin-bottom: 10px; padding-left: 30px; display: flex; gap: 16px; - F
Gujarati Call Center Data for Travel AI
- futurebeeai.com
wavUpdated Aug 1, 2022ShareFacebookTwitterEmailClick to copy linkLink copiedCiteFutureBee AI (2022). Gujarati Call Center Data for Travel AI [Dataset]. https://www.futurebeeai.com/dataset/speech-dataset/travel-call-center-conversation-gujarati-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 Gujarati Call Center Speech Dataset for the Travel industry is purpose-built to power the next generation of voice AI applications for travel booking, customer support, and itinerary assistance. With over 30 hours of unscripted, real-world conversations, the dataset enables the development of highly accurate speech recognition and natural language understanding models tailored for Gujarati -speaking travelers.
Created by FutureBeeAI, this dataset supports researchers, data scientists, and conversational AI teams in building voice technologies for airlines, travel portals, and hospitality platforms.
Speech Data
The dataset includes 30 hours of dual-channel audio recordings between native Gujarati speakers engaged in real travel-related customer service conversations. These audio files reflect a wide variety of topics, accents, and scenarios found across the travel and tourism industry.
•Participant Diversity:•Speakers: 60 native Gujarati contributors from our verified pool.•Regions: Covering multiple Gujarat regions to capture accent and dialectal variation.•Participant Profile: Balanced representation of age (18–70) and gender (60% male, 40% female).•Recording Details:•Conversation Nature: Naturally flowing, spontaneous customer-agent calls.•Call Duration: Between 5 and 15 minutes per session.•Audio Format: Stereo WAV, 16-bit depth, at 8kHz and 16kHz.•Recording Environment: Captured in controlled, noise-free, echo-free settings.Topic Diversity
Inbound and outbound conversations span a wide range of real-world travel support situations with varied outcomes (positive, neutral, negative).
•Inbound Calls:•Booking Assistance•Destination Information•Flight Delays or Cancellations•Support for Disabled Passengers•Health and Safety Travel Inquiries•Lost or Delayed Luggage, and more•Outbound Calls:•Promotional Travel Offers•Customer Feedback Surveys•Booking Confirmations•Flight Rescheduling Alerts•Visa Expiry Notifications, and othersThese scenarios help models understand and respond to diverse traveler needs in real-time.
Transcription
Each call is accompanied by manually curated, high-accuracy transcriptions in JSON format.
•Transcription Includes:•Speaker-Segmented Dialogues•Time-Stamped Segments•Non-speech Markers (e.g., pauses, coughs)•High transcription accuracy by dual-layered transcription review ensures word error rate under 5%.Metadata
Extensive metadata enriches each call and speaker for better filtering and AI training:
•Participant Metadata: ID, age, gender, region, accent, and dialect.•Conversation Metadata: Topic, domain, call type, sentiment, and audio specs.Usage and Applications
This dataset is ideal for a variety of AI use cases in the travel and tourism space:
•ASR Systems: Train Gujarati speech-to-text engines for travel platforms.<div style="margin-top:10px; margin-bottom: 10px; padding-left: 30px; display: - F
Hindi Call Center Data for Travel AI
- futurebeeai.com
wavUpdated Aug 1, 2022ShareFacebookTwitterEmailClick to copy linkLink copiedCiteFutureBee AI (2022). Hindi Call Center Data for Travel AI [Dataset]. https://www.futurebeeai.com/dataset/speech-dataset/travel-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 Travel industry is purpose-built to power the next generation of voice AI applications for travel booking, customer support, and itinerary assistance. With over 30 hours of unscripted, real-world conversations, the dataset enables the development of highly accurate speech recognition and natural language understanding models tailored for Hindi -speaking travelers.
Created by FutureBeeAI, this dataset supports researchers, data scientists, and conversational AI teams in building voice technologies for airlines, travel portals, and hospitality platforms.
Speech Data
The dataset includes 30 hours of dual-channel audio recordings between native Hindi speakers engaged in real travel-related customer service conversations. These audio files reflect a wide variety of topics, accents, and scenarios found across the travel and tourism industry.
•Participant Diversity:•Speakers: 60 native Hindi contributors from our verified pool.•Regions: Covering multiple India provinces to capture accent and dialectal variation.•Participant Profile: Balanced representation of age (18–70) and gender (60% male, 40% female).•Recording Details:•Conversation Nature: Naturally flowing, spontaneous customer-agent calls.•Call Duration: Between 5 and 15 minutes per session.•Audio Format: Stereo WAV, 16-bit depth, at 8kHz and 16kHz.•Recording Environment: Captured in controlled, noise-free, echo-free settings.Topic Diversity
Inbound and outbound conversations span a wide range of real-world travel support situations with varied outcomes (positive, neutral, negative).
•Inbound Calls:•Booking Assistance•Destination Information•Flight Delays or Cancellations•Support for Disabled Passengers•Health and Safety Travel Inquiries•Lost or Delayed Luggage, and more•Outbound Calls:•Promotional Travel Offers•Customer Feedback Surveys•Booking Confirmations•Flight Rescheduling Alerts•Visa Expiry Notifications, and othersThese scenarios help models understand and respond to diverse traveler needs in real-time.
Transcription
Each call is accompanied by manually curated, high-accuracy transcriptions in JSON format.
•Transcription Includes:•Speaker-Segmented Dialogues•Time-Stamped Segments•Non-speech Markers (e.g., pauses, coughs)•High transcription accuracy by dual-layered transcription review ensures word error rate under 5%.Metadata
Extensive metadata enriches each call and speaker for better filtering and AI training:
•Participant Metadata: ID, age, gender, region, accent, and dialect.•Conversation Metadata: Topic, domain, call type, sentiment, and audio specs.Usage and Applications
This dataset is ideal for a variety of AI use cases in the travel and tourism space:
•ASR Systems: Train Hindi speech-to-text engines for travel platforms.<div style="margin-top:10px; margin-bottom: 10px; padding-left: 30px; display: flex; gap: 16px; - F
Indian English Call Center Data for Travel AI
- futurebeeai.com
wavUpdated Aug 1, 2022ShareFacebookTwitterEmailClick to copy linkLink copiedCiteFutureBee AI (2022). Indian English Call Center Data for Travel AI [Dataset]. https://www.futurebeeai.com/dataset/speech-dataset/travel-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
Area coveredIndiaDataset funded byFutureBeeAIDescriptionIntroduction
This Indian English Call Center Speech Dataset for the Travel industry is purpose-built to power the next generation of voice AI applications for travel booking, customer support, and itinerary assistance. With over 30 hours of unscripted, real-world conversations, the dataset enables the development of highly accurate speech recognition and natural language understanding models tailored for English -speaking travelers.
Created by FutureBeeAI, this dataset supports researchers, data scientists, and conversational AI teams in building voice technologies for airlines, travel portals, and hospitality platforms.
Speech Data
The dataset includes 30 hours of dual-channel audio recordings between native Indian English speakers engaged in real travel-related customer service conversations. These audio files reflect a wide variety of topics, accents, and scenarios found across the travel and tourism industry.
•Participant Diversity:•Speakers: 60 native Indian English contributors from our verified pool.•Regions: Covering multiple India provinces to capture accent and dialectal variation.•Participant Profile: Balanced representation of age (18–70) and gender (60% male, 40% female).•Recording Details:•Conversation Nature: Naturally flowing, spontaneous customer-agent calls.•Call Duration: Between 5 and 15 minutes per session.•Audio Format: Stereo WAV, 16-bit depth, at 8kHz and 16kHz.•Recording Environment: Captured in controlled, noise-free, echo-free settings.Topic Diversity
Inbound and outbound conversations span a wide range of real-world travel support situations with varied outcomes (positive, neutral, negative).
•Inbound Calls:•Booking Assistance•Destination Information•Flight Delays or Cancellations•Support for Disabled Passengers•Health and Safety Travel Inquiries•Lost or Delayed Luggage, and more•Outbound Calls:•Promotional Travel Offers•Customer Feedback Surveys•Booking Confirmations•Flight Rescheduling Alerts•Visa Expiry Notifications, and othersThese scenarios help models understand and respond to diverse traveler needs in real-time.
Transcription
Each call is accompanied by manually curated, high-accuracy transcriptions in JSON format.
•Transcription Includes:•Speaker-Segmented Dialogues•Time-Stamped Segments•Non-speech Markers (e.g., pauses, coughs)•High transcription accuracy by dual-layered transcription review ensures word error rate under 5%.Metadata
Extensive metadata enriches each call and speaker for better filtering and AI training:
•Participant Metadata: ID, age, gender, region, accent, and dialect.•Conversation Metadata: Topic, domain, call type, sentiment, and audio specs.Usage and Applications
This dataset is ideal for a variety of AI use cases in the travel and tourism space:
•ASR Systems: Train English speech-to-text engines for travel platforms.<div style="margin-top:10px; margin-bottom: 10px; padding-left: 
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Introduction
This Bahasa Call Center Speech Dataset for the Travel industry is purpose-built to power the next generation of voice AI applications for travel booking, customer support, and itinerary assistance. With over 40 hours of unscripted, real-world conversations, the dataset enables the development of highly accurate speech recognition and natural language understanding models tailored for Bahasa -speaking travelers.
Created by FutureBeeAI, this dataset supports researchers, data scientists, and conversational AI teams in building voice technologies for airlines, travel portals, and hospitality platforms.
Speech Data
The dataset includes 40 hours of dual-channel audio recordings between native Bahasa speakers engaged in real travel-related customer service conversations. These audio files reflect a wide variety of topics, accents, and scenarios found across the travel and tourism industry.
Topic Diversity
Inbound and outbound conversations span a wide range of real-world travel support situations with varied outcomes (positive, neutral, negative).
These scenarios help models understand and respond to diverse traveler needs in real-time.
Transcription
Each call is accompanied by manually curated, high-accuracy transcriptions in JSON format.
Metadata
Extensive metadata enriches each call and speaker for better filtering and AI training:
Usage and Applications
This dataset is ideal for a variety of AI use cases in the travel and tourism space: