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Mexican Spanish Call Center Data for Telecom AI
- futurebeeai.com
wavUpdated Aug 1, 2022
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EmailClick to copy linkLink copiedCiteFutureBee AI (2022). Mexican Spanish Call Center Data for Telecom AI [Dataset]. https://www.futurebeeai.com/dataset/speech-dataset/telecom-call-center-conversation-spanish-mexicowavAvailable 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 coveredMexicoDataset funded byFutureBeeAIDescriptionIntroduction
This Mexican Spanish 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 Spanish-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 Mexican Spanish 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 Mexican Spanish speakers from our verified contributor pool.•Regions: Representing multiple provinces across Mexico 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
Spanish (Spain) Call Center Data for Telecom AI
- futurebeeai.com
wavUpdated Aug 1, 2022ShareFacebookTwitterEmailClick to copy linkLink copiedCiteFutureBee AI (2022). Spanish (Spain) Call Center Data for Telecom AI [Dataset]. https://www.futurebeeai.com/dataset/speech-dataset/telecom-call-center-conversation-spanish-spainwavAvailable 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 Spanish 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 Spanish-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 Spanish 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 Spanish speakers from our verified contributor pool.•Regions: Representing multiple provinces across Spain 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
US Spanish Call Center Data for Telecom AI
- futurebeeai.com
wavUpdated Aug 1, 2022ShareFacebookTwitterEmailClick to copy linkLink copiedCiteFutureBee AI (2022). US Spanish Call Center Data for Telecom AI [Dataset]. https://www.futurebeeai.com/dataset/speech-dataset/telecom-call-center-conversation-spanish-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 Spanish 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 Spanish-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 Spanish 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 Spanish speakers from our verified contributor pool.•Regions: Representing multiple provinces across USA 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
Colombian Spanish Call Center Data for Telecom AI
- futurebeeai.com
wavUpdated Aug 1, 2022ShareFacebookTwitterEmailClick to copy linkLink copiedCiteFutureBee AI (2022). Colombian Spanish Call Center Data for Telecom AI [Dataset]. https://www.futurebeeai.com/dataset/speech-dataset/telecom-call-center-conversation-spanish-colombiawavAvailable 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 Colombian Spanish 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 Spanish-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 Colombian Spanish 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 Colombian Spanish speakers from our verified contributor pool.•Regions: Representing multiple provinces across Colombia 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: 
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Mexican Spanish 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 Mexican Spanish 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 Spanish-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 Mexican Spanish 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: