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American English Call Center Data for Telecom AI
- futurebeeai.com
wavUpdated Aug 1, 2022
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EmailClick to copy linkLink copiedCiteFutureBee AI (2022). American English Call Center Data for Telecom AI [Dataset]. https://www.futurebeeai.com/dataset/speech-dataset/telecom-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 Telecom industry is purpose-built to accelerate the development of speech recognition, spoken language understanding, and conversational AI systems tailored for English-speaking telecom customers. Featuring over 30 hours of real-world, unscripted audio, it delivers authentic customer-agent interactions across key telecom support scenarios to help train robust ASR models.
Curated by FutureBeeAI, this dataset empowers voice AI engineers, telecom automation teams, and NLP researchers to build high-accuracy, production-ready models for telecom-specific use cases.
Speech Data
The dataset contains 30 hours of dual-channel call center recordings between native US English speakers. Captured in realistic customer support settings, these conversations span a wide range of telecom topics from network complaints to billing issues, offering a strong foundation for training and evaluating telecom voice AI solutions.
•Participant Diversity:•Speakers: 60 native US English speakers from our verified contributor pool.•Regions: Representing multiple provinces across United States of America to ensure coverage of various accents and dialects.•Participant Profile: Balanced gender mix (60% male, 40% female) with age distribution from 18 to 70 years.•Recording Details:•Conversation Nature: Naturally flowing, unscripted interactions between agents and customers.•Call Duration: Ranges from 5 to 15 minutes.•Audio Format: Stereo WAV files, 16-bit depth, at 8kHz and 16kHz sample rates.•Recording Environment: Captured in clean conditions with no echo or background noise.Topic Diversity
This speech corpus includes both inbound and outbound calls with varied conversational outcomes like positive, negative, and neutral ensuring broad scenario coverage for telecom AI development.
•Inbound Calls:•Phone Number Porting•Network Connectivity Issues•Billing and Payments•Technical Support•Service Activation•International Roaming Enquiry•Refund Requests and Billing Adjustments•Emergency Service Access, and others•Outbound Calls:•Welcome Calls & Onboarding•Payment Reminders•Customer Satisfaction Surveys•Technical Updates•Service Usage Reviews•Network Complaint Status Calls, and moreThis variety helps train telecom-specific models to manage real-world customer interactions and understand context-specific voice patterns.
Transcription
All audio files are accompanied by manually curated, time-coded verbatim transcriptions in JSON format.
•Transcription Includes:•Speaker-Segmented Dialogues•Time-coded Segments•Non-speech Tags (e.g., pauses, coughs)•High transcription accuracy with word error rate < 5% thanks to dual-layered quality checks.These transcriptions are production-ready, allowing for faster development of ASR and conversational AI systems in the Telecom domain.
Metadata
Rich metadata is available for each participant and conversation:
•Participant Metadata: ID, age, gender, accent, dialect, and location.<div style="margin-top:10px; margin-bottom: 10px; padding-left: 30px; display: flex; gap: 16px; - F
Canadian English Call Center Data for Telecom AI
- futurebeeai.com
wavUpdated Aug 1, 2022ShareFacebookTwitterEmailClick to copy linkLink copiedCiteFutureBee AI (2022). Canadian English Call Center Data for Telecom AI [Dataset]. https://www.futurebeeai.com/dataset/speech-dataset/telecom-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 Telecom industry is purpose-built to accelerate the development of speech recognition, spoken language understanding, and conversational AI systems tailored for English-speaking telecom customers. Featuring over 30 hours of real-world, unscripted audio, it delivers authentic customer-agent interactions across key telecom support scenarios to help train robust ASR models.
Curated by FutureBeeAI, this dataset empowers voice AI engineers, telecom automation teams, and NLP researchers to build high-accuracy, production-ready models for telecom-specific use cases.
Speech Data
The dataset contains 30 hours of dual-channel call center recordings between native Canadian English speakers. Captured in realistic customer support settings, these conversations span a wide range of telecom topics from network complaints to billing issues, offering a strong foundation for training and evaluating telecom voice AI solutions.
•Participant Diversity:•Speakers: 60 native Canadian English speakers from our verified contributor pool.•Regions: Representing multiple provinces across Canada to ensure coverage of various accents and dialects.•Participant Profile: Balanced gender mix (60% male, 40% female) with age distribution from 18 to 70 years.•Recording Details:•Conversation Nature: Naturally flowing, unscripted interactions between agents and customers.•Call Duration: Ranges from 5 to 15 minutes.•Audio Format: Stereo WAV files, 16-bit depth, at 8kHz and 16kHz sample rates.•Recording Environment: Captured in clean conditions with no echo or background noise.Topic Diversity
This speech corpus includes both inbound and outbound calls with varied conversational outcomes like positive, negative, and neutral ensuring broad scenario coverage for telecom AI development.
•Inbound Calls:•Phone Number Porting•Network Connectivity Issues•Billing and Payments•Technical Support•Service Activation•International Roaming Enquiry•Refund Requests and Billing Adjustments•Emergency Service Access, and others•Outbound Calls:•Welcome Calls & Onboarding•Payment Reminders•Customer Satisfaction Surveys•Technical Updates•Service Usage Reviews•Network Complaint Status Calls, and moreThis variety helps train telecom-specific models to manage real-world customer interactions and understand context-specific voice patterns.
Transcription
All audio files are accompanied by manually curated, time-coded verbatim transcriptions in JSON format.
•Transcription Includes:•Speaker-Segmented Dialogues•Time-coded Segments•Non-speech Tags (e.g., pauses, coughs)•High transcription accuracy with word error rate < 5% thanks to dual-layered quality checks.These transcriptions are production-ready, allowing for faster development of ASR and conversational AI systems in the Telecom domain.
Metadata
Rich metadata is available for each participant and conversation:
•Participant Metadata: ID, age, gender, accent, dialect, and location.<div style="margin-top:10px; margin-bottom: 10px; padding-left: 30px; display: flex; gap: 16px; - F
Hindi Call Center Data for Telecom AI
- futurebeeai.com
wavUpdated Aug 1, 2022ShareFacebookTwitterEmailClick to copy linkLink copiedCiteFutureBee AI (2022). Hindi Call Center Data for Telecom AI [Dataset]. https://www.futurebeeai.com/dataset/speech-dataset/telecom-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 Telecom industry is purpose-built to accelerate the development of speech recognition, spoken language understanding, and conversational AI systems tailored for Hindi-speaking telecom customers. Featuring over 30 hours of real-world, unscripted audio, it delivers authentic customer-agent interactions across key telecom support scenarios to help train robust ASR models.
Curated by FutureBeeAI, this dataset empowers voice AI engineers, telecom automation teams, and NLP researchers to build high-accuracy, production-ready models for telecom-specific use cases.
Speech Data
The dataset contains 30 hours of dual-channel call center recordings between native Hindi speakers. Captured in realistic customer support settings, these conversations span a wide range of telecom topics from network complaints to billing issues, offering a strong foundation for training and evaluating telecom voice AI solutions.
•Participant Diversity:•Speakers: 60 native Hindi speakers from our verified contributor pool.•Regions: Representing multiple provinces across India to ensure coverage of various accents and dialects.•Participant Profile: Balanced gender mix (60% male, 40% female) with age distribution from 18 to 70 years.•Recording Details:•Conversation Nature: Naturally flowing, unscripted interactions between agents and customers.•Call Duration: Ranges from 5 to 15 minutes.•Audio Format: Stereo WAV files, 16-bit depth, at 8kHz and 16kHz sample rates.•Recording Environment: Captured in clean conditions with no echo or background noise.Topic Diversity
This speech corpus includes both inbound and outbound calls with varied conversational outcomes like positive, negative, and neutral ensuring broad scenario coverage for telecom AI development.
•Inbound Calls:•Phone Number Porting•Network Connectivity Issues•Billing and Payments•Technical Support•Service Activation•International Roaming Enquiry•Refund Requests and Billing Adjustments•Emergency Service Access, and others•Outbound Calls:•Welcome Calls & Onboarding•Payment Reminders•Customer Satisfaction Surveys•Technical Updates•Service Usage Reviews•Network Complaint Status Calls, and moreThis variety helps train telecom-specific models to manage real-world customer interactions and understand context-specific voice patterns.
Transcription
All audio files are accompanied by manually curated, time-coded verbatim transcriptions in JSON format.
•Transcription Includes:•Speaker-Segmented Dialogues•Time-coded Segments•Non-speech Tags (e.g., pauses, coughs)•High transcription accuracy with word error rate < 5% thanks to dual-layered quality checks.These transcriptions are production-ready, allowing for faster development of ASR and conversational AI systems in the Telecom domain.
Metadata
Rich metadata is available for each participant and conversation:
•Participant Metadata: ID, age, gender, accent, dialect, and location. - F
British English Call Center Data for Telecom AI
- futurebeeai.com
wavUpdated Aug 1, 2022ShareFacebookTwitterEmailClick to copy linkLink copiedCiteFutureBee AI (2022). British English Call Center Data for Telecom AI [Dataset]. https://www.futurebeeai.com/dataset/speech-dataset/telecom-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
Area coveredUnited KingdomDataset funded byFutureBeeAIDescriptionIntroduction
This UK English Call Center Speech Dataset for the Telecom industry is purpose-built to accelerate the development of speech recognition, spoken language understanding, and conversational AI systems tailored for English-speaking telecom customers. Featuring over 30 hours of real-world, unscripted audio, it delivers authentic customer-agent interactions across key telecom support scenarios to help train robust ASR models.
Curated by FutureBeeAI, this dataset empowers voice AI engineers, telecom automation teams, and NLP researchers to build high-accuracy, production-ready models for telecom-specific use cases.
Speech Data
The dataset contains 30 hours of dual-channel call center recordings between native UK English speakers. Captured in realistic customer support settings, these conversations span a wide range of telecom topics from network complaints to billing issues, offering a strong foundation for training and evaluating telecom voice AI solutions.
•Participant Diversity:•Speakers: 60 native UK English speakers from our verified contributor pool.•Regions: Representing multiple provinces across United Kingdom to ensure coverage of various accents and dialects.•Participant Profile: Balanced gender mix (60% male, 40% female) with age distribution from 18 to 70 years.•Recording Details:•Conversation Nature: Naturally flowing, unscripted interactions between agents and customers.•Call Duration: Ranges from 5 to 15 minutes.•Audio Format: Stereo WAV files, 16-bit depth, at 8kHz and 16kHz sample rates.•Recording Environment: Captured in clean conditions with no echo or background noise.Topic Diversity
This speech corpus includes both inbound and outbound calls with varied conversational outcomes like positive, negative, and neutral ensuring broad scenario coverage for telecom AI development.
•Inbound Calls:•Phone Number Porting•Network Connectivity Issues•Billing and Payments•Technical Support•Service Activation•International Roaming Enquiry•Refund Requests and Billing Adjustments•Emergency Service Access, and others•Outbound Calls:•Welcome Calls & Onboarding•Payment Reminders•Customer Satisfaction Surveys•Technical Updates•Service Usage Reviews•Network Complaint Status Calls, and moreThis variety helps train telecom-specific models to manage real-world customer interactions and understand context-specific voice patterns.
Transcription
All audio files are accompanied by manually curated, time-coded verbatim transcriptions in JSON format.
•Transcription Includes:•Speaker-Segmented Dialogues•Time-coded Segments•Non-speech Tags (e.g., pauses, coughs)•High transcription accuracy with word error rate < 5% thanks to dual-layered quality checks.These transcriptions are production-ready, allowing for faster development of ASR and conversational AI systems in the Telecom domain.
Metadata
Rich metadata is available for each participant and conversation:
•Participant Metadata: ID, age, gender, accent, dialect, and location.<div style="margin-top:10px; margin-bottom: 10px; padding-left: 30px; display: flex; gap: 16px; align-items: - F
Indian English Call Center Data for Telecom AI
- futurebeeai.com
wavUpdated Aug 1, 2022ShareFacebookTwitterEmailClick to copy linkLink copiedCiteFutureBee AI (2022). Indian English Call Center Data for Telecom AI [Dataset]. https://www.futurebeeai.com/dataset/speech-dataset/telecom-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 Telecom industry is purpose-built to accelerate the development of speech recognition, spoken language understanding, and conversational AI systems tailored for English-speaking telecom customers. Featuring over 30 hours of real-world, unscripted audio, it delivers authentic customer-agent interactions across key telecom support scenarios to help train robust ASR models.
Curated by FutureBeeAI, this dataset empowers voice AI engineers, telecom automation teams, and NLP researchers to build high-accuracy, production-ready models for telecom-specific use cases.
Speech Data
The dataset contains 30 hours of dual-channel call center recordings between native Indian English speakers. Captured in realistic customer support settings, these conversations span a wide range of telecom topics from network complaints to billing issues, offering a strong foundation for training and evaluating telecom voice AI solutions.
•Participant Diversity:•Speakers: 60 native Indian English speakers from our verified contributor pool.•Regions: Representing multiple provinces across India to ensure coverage of various accents and dialects.•Participant Profile: Balanced gender mix (60% male, 40% female) with age distribution from 18 to 70 years.•Recording Details:•Conversation Nature: Naturally flowing, unscripted interactions between agents and customers.•Call Duration: Ranges from 5 to 15 minutes.•Audio Format: Stereo WAV files, 16-bit depth, at 8kHz and 16kHz sample rates.•Recording Environment: Captured in clean conditions with no echo or background noise.Topic Diversity
This speech corpus includes both inbound and outbound calls with varied conversational outcomes like positive, negative, and neutral ensuring broad scenario coverage for telecom AI development.
•Inbound Calls:•Phone Number Porting•Network Connectivity Issues•Billing and Payments•Technical Support•Service Activation•International Roaming Enquiry•Refund Requests and Billing Adjustments•Emergency Service Access, and others•Outbound Calls:•Welcome Calls & Onboarding•Payment Reminders•Customer Satisfaction Surveys•Technical Updates•Service Usage Reviews•Network Complaint Status Calls, and moreThis variety helps train telecom-specific models to manage real-world customer interactions and understand context-specific voice patterns.
Transcription
All audio files are accompanied by manually curated, time-coded verbatim transcriptions in JSON format.
•Transcription Includes:•Speaker-Segmented Dialogues•Time-coded Segments•Non-speech Tags (e.g., pauses, coughs)•High transcription accuracy with word error rate < 5% thanks to dual-layered quality checks.These transcriptions are production-ready, allowing for faster development of ASR and conversational AI systems in the Telecom domain.
Metadata
Rich metadata is available for each participant and conversation:
•Participant Metadata: ID, age, gender, accent, dialect, and location.<div style="margin-top:10px; margin-bottom: 10px; padding-left: 30px; display: flex; gap: 16px; 
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American English call center speech corpus in telecom industry
https://www.futurebeeai.com/policies/ai-data-license-agreementhttps://www.futurebeeai.com/policies/ai-data-license-agreement
Introduction
This US English Call Center Speech Dataset for the Telecom industry is purpose-built to accelerate the development of speech recognition, spoken language understanding, and conversational AI systems tailored for English-speaking telecom customers. Featuring over 30 hours of real-world, unscripted audio, it delivers authentic customer-agent interactions across key telecom support scenarios to help train robust ASR models.
Curated by FutureBeeAI, this dataset empowers voice AI engineers, telecom automation teams, and NLP researchers to build high-accuracy, production-ready models for telecom-specific use cases.
Speech Data
The dataset contains 30 hours of dual-channel call center recordings between native US English speakers. Captured in realistic customer support settings, these conversations span a wide range of telecom topics from network complaints to billing issues, offering a strong foundation for training and evaluating telecom voice AI solutions.
Topic Diversity
This speech corpus includes both inbound and outbound calls with varied conversational outcomes like positive, negative, and neutral ensuring broad scenario coverage for telecom AI development.
This variety helps train telecom-specific models to manage real-world customer interactions and understand context-specific voice patterns.
Transcription
All audio files are accompanied by manually curated, time-coded verbatim transcriptions in JSON format.
These transcriptions are production-ready, allowing for faster development of ASR and conversational AI systems in the Telecom domain.
Metadata
Rich metadata is available for each participant and conversation: