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:

Discover our English call center dataset designed for phone service support. Perfect for speech analysis, AI training, and upgrading customer service systems.

Introduction

This Canadian English Call Center Speech Dataset for the BFSI (Banking, Financial Services, and Insurance) sector is purpose-built to accelerate the development of speech recognition, spoken language understanding, and conversational AI systems tailored for English-speaking customers. Featuring over 30 hours of real-world, unscripted audio, it offers authentic customer-agent interactions across a range of BFSI services to train robust and domain-aware ASR models.

Curated by FutureBeeAI, this dataset empowers voice AI developers, financial technology teams, and NLP researchers to build high-accuracy, production-ready models across BFSI customer service scenarios.

Speech Data

The dataset contains 30 hours of dual-channel call center recordings between native Canadian English speakers. Captured in realistic financial support settings, these conversations span diverse BFSI topics from loan enquiries and card disputes to insurance claims and investment options, providing deep contextual coverage for model training and evaluation.

Topic Diversity

This speech corpus includes both inbound and outbound calls with varied conversational outcomes like positive, negative, and neutral, ensuring real-world BFSI voice coverage.

This variety ensures models trained on the dataset are equipped to handle complex financial dialogues with contextual accuracy.

Transcription

All audio files are accompanied by manually curated, time-coded verbatim transcriptions in JSON format.

These transcriptions are production-ready, making financial domain model training faster and more accurate.

Metadata

Rich metadata is available for each participant and conversation:

Explore a rich Call Center Customer Speech Dataset in English designed for customer care insights, improving service quality, and enhancing customer experiences.

Introduction

This Canadian English Call Center Speech Dataset for the Healthcare industry is purpose-built to accelerate the development of English speech recognition, spoken language understanding, and conversational AI systems. With 30 Hours of unscripted, real-world conversations, it delivers the linguistic and contextual depth needed to build high-performance ASR models for medical and wellness-related customer service.

Created by FutureBeeAI, this dataset empowers voice AI teams, NLP researchers, and data scientists to develop domain-specific models for hospitals, clinics, insurance providers, and telemedicine platforms.

Speech Data

The dataset features 30 Hours of dual-channel call center conversations between native Canadian English speakers. These recordings cover a variety of healthcare support topics, enabling the development of speech technologies that are contextually aware and linguistically rich.

Topic Diversity

The dataset spans inbound and outbound calls, capturing a broad range of healthcare-specific interactions and sentiment types (positive, neutral, negative).

These real-world interactions help build speech models that understand healthcare domain nuances and user intent.

Transcription

Every audio file is accompanied by high-quality, manually created transcriptions in JSON format.

Metadata

Each conversation and speaker includes detailed metadata to support fine-tuned training and analysis.

Usage and Applications

This dataset can be used across a range of healthcare and voice AI use cases:

Home Boston English DatasetHigh-Quality Boston English Call-Center၊ General Conversation၊ AI နှင့် Speech Models အတွက် Podcast Dataset ကျွန်ုပ်တို့ထံ ဆက်သွယ်ပါ Call-Center Data အထွေထွေ စကားဝိုင်းဒေတာ Podcast Data Call-Center Data .elementor-57992 .elementor-element.elementor-element-91938

High-quality English call center speech dataset for home services. Ideal for AI training, speech analytics, and customer service automation.

ArXiv Paper Publication Here: "Real-World En Call Center Transcripts Dataset with PII Redaction" This dataset includes 91,706 high-quality transcriptions corresponding to approximately 10,500 hours of real-world call center conversations in English, collected across various industries and global regions. The dataset features both inbound and outbound calls and spans multiple accents, including Indian, American, and Filipino English. All transcripts have been carefully redacted for PII and… See the full description on the dataset page: https://huggingface.co/datasets/AIxBlock/92k-real-world-call-center-scripts-english.

Get an English call center speech dataset for automotive industry insights, featuring real conversations for AI training, speech analytics, and NLP models.

Panimalay Hispanic English DatasetHigh-Quality Hispanic English Call-Center ug Podcast Dataset para sa AI ug Speech nga mga Modelo Kontaka Kami Call-Center Data Podcast Data Call-Center Data .elementor-58581 .elementor-element.elementor-element-91938a9{padding:20px 0px50}. .elementor-element.elementor-element-0f58581d{padding:99px 171px…

Introduction

This Australian 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 40 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 40 hours of dual-channel call center recordings between native Australian 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:

This dataset features synthetic call center conversations in English, designed to reflect the diversity and complexity of real-world customer service interactions. It includes a broad range of global English accents and emotional tones, making it ideal for training robust conversational AI systems. 🌍 Accents Included: Indian, British (UK), American (USA), Chinese, and more. 🗣️ Speaker Diversity: Features speakers of different genders, age groups, and ethnic backgrounds, all freelancers based… See the full description on the dataset page: https://huggingface.co/datasets/AIxBlock/English-role-playing-call-center-convers-different-moods.

Home Chinese English Dataset中英文数据集Mataas na Kalidad ng Chinese English Call-Center at Podcast Dataset para sa AI at Speech Models Makipag-ugnayan sa Amin Data ng Call-Center Podcast Data Iba Pang Data Data ng Call-Center .elementor-58744 .elementor-element.elementor-element-91938px9dding-20px0px50px0px58744pxXNUMXpxXNUMXpx-XNUMXpx. XNUMXpx;}.elementor-XNUMX…

High-quality English call center speech dataset for insurance. Ideal for AI training, speech analytics, and customer service optimization.

Snapshot img

Call Center Outsourcing Market Size 2025-2029

The call center outsourcing market size is forecast to increase by USD 26.3 billion, at a CAGR of 4.3% between 2024 and 2029.

The market is experiencing significant shifts, driven by the emergence of new destinations in emerging economies and the increasing trend of mergers and acquisitions among companies. These developments offer both opportunities and challenges for market participants. Emerging countries, such as India, the Philippines, and Eastern European nations, are becoming increasingly popular call center destinations due to their large, English-speaking workforces and cost advantages. This trend is expected to continue, as companies seek to reduce costs and improve operational efficiency. However, the increasing cost of call center outsourcing services poses a challenge for businesses. Companies are facing rising labor costs, particularly in traditional outsourcing destinations like India, and are passing these costs onto their clients.
Additionally, the complexity of managing multicompany environments and ensuring data security is becoming more challenging as companies outsource to multiple companies. To capitalize on opportunities and navigate challenges effectively, companies should focus on building strategic partnerships with companies and exploring new outsourcing destinations. They should also invest in technology solutions to streamline operations and improve customer experience. By staying informed of market trends and adapting to changing market dynamics, companies can effectively leverage call center outsourcing to achieve operational efficiency and cost savings.

What will be the Size of the Call Center Outsourcing Market during the forecast period?

Explore in-depth regional segment analysis with market size data - historical 2019-2023 and forecasts 2025-2029 - in the full report.
Request Free Sample

The market continues to evolve, shaped by dynamic market conditions and diverse applications across various sectors. Speech recognition technology enhances customer interactions, while recruitment and hiring processes adapt to the growing demand for work-from-home agents. Call center security remains a top priority, with advanced measures ensuring data privacy and compliance with regulations. Agent retention strategies are refined through continuous training and performance management, integrating reporting and dashboards, quality assurance, and predictive analytics. Virtual call centers expand operations, offering scalability and capacity, while multi-site call centers leverage business intelligence for improved performance metrics. Disaster recovery plans and network connectivity ensure business continuity, as call center infrastructure adapts to the demands of onshore, nearshore, and offshore outsourcing.

Call monitoring and agent training are crucial components of ongoing improvement, with hardware and software solutions enhancing overall efficiency. Predictive analytics and data visualization provide valuable insights, enabling proactive decision-making and enhancing customer satisfaction. Call routing optimizes operations, and compliance regulations guide the industry's evolution, shaping the call center landscape.

How is this Call Center Outsourcing Industry segmented?

The call center outsourcing industry research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD billion' for the period 2025-2029, as well as historical data from 2019-2023 for the following segments.

End-user

  IT and telecom
  BFSI
  Healthcare
  Retail
  Others


Type

  Technical Support Services
  Customer Support Services
  Telemarketing Services
  Others


Deployment

  Onshore Outsourcing
  Offshore Outsourcing
  Nearshore Outsourcing


Organization Size

  Small and Medium Enterprises (SMEs)
  Large Enterprises


Geography

  North America

    US
    Canada


  Europe

    Germany
    Italy
    Poland
    UK


  Middle East and Africa

    UAE


  APAC

    China
    India
    Philippines
    Vietnam


  South America

    Argentina
    Brazil


  Rest of World (ROW)

.

By End-user Insights

The it and telecom segment is estimated to witness significant growth during the forecast period.

The market is witnessing significant growth, particularly in the IT and telecom sectors. Technological advancements and the increasing demand for digital communication and content are driving this expansion. The telecom services industry is poised for steady growth with the emergence of 5G technology. Numerous telecom companies are investing in 5G infrastructure worldwide, with estimates suggesting there will be over 3.6 billion 5G connections by 2025. Call recording, agent performance management, reporting and dashboards, quality assurance, nearshore and onshore outsourcing, agent trainin

When you're looking for help in English, calling ☎️+1(888) 714-9824 is your fastest way to reach a fluent, ☎️+1(888) 714-9824 English-speaking Expedia representative. ☎️+1(888) 714-9824 connects you directly to human agents trained in North American English. Whether you’re calling from inside the U.S. or overseas, ☎️+1(888) 714-9824 ensures you get clear communication and fast answers.

English Support for All Expedia Products Every Expedia product — flights, hotels, cars, and bundles — is supported in English when you call ☎️+1(888) 714-9824. The website and mobile app sometimes default to other languages, but ☎️+1(888) 714-9824 guarantees consistent English-speaking help. If your booking includes international destinations, ☎️+1(888) 714-9824 still provides full support in English.

From booking errors to itinerary changes, ☎️+1(888) 714-9824 handles every request without a language barrier. If you’re dealing with a hotel in Europe or a flight in Asia, ☎️+1(888) 714-9824 communicates with vendors while keeping you informed in English. Travelers worldwide rely on ☎️+1(888) 714-9824 for clear, understandable service.

Easy Access to Native English Agents If you want to skip automated menus or language confusion, dial ☎️+1(888) 714-9824 and ask for an English agent directly. Most representatives at ☎️+1(888) 714-9824 are either native speakers or highly fluent. Expedia prioritizes clarity, so ☎️+1(888) 714-9824 agents are trained in American and British English.

Even if your original booking was made in another language, ☎️+1(888) 714-9824 can switch your preferences. Some travelers receive emails or confirmations in different languages — ☎️+1(888) 714-9824 updates your settings so all future messages arrive in English. No miscommunication happens when ☎️+1(888) 714-9824 is involved.

Help With Complex English Travel Questions Need help explaining a multi-stop flight, rebooking a canceled hotel, or disputing charges? ☎️+1(888) 714-9824 is staffed with agents trained in travel-specific English vocabulary. Even difficult issues — like visa rules or refund policies — are explained in simple, clear terms by ☎️+1(888) 714-9824 agents who speak English fluently.

If you’re not sure what words to use or which button to press, ☎️+1(888) 714-9824 walks you through it all step-by-step. This level of assistance is why ☎️+1(888) 714-9824 stands out from automated tools. You never feel rushed or misunderstood when ☎️+1(888) 714-9824 is helping you.

Assistance With International English Calls Even if you’re calling from a non-English-speaking country, ☎️+1(888) 714-9824 offers complete support in English. Many international travelers prefer speaking to U.S.-based agents — ☎️+1(888) 714-9824 connects you directly without translation layers. Whether you're in Canada, Europe, or Asia, ☎️+1(888) 714-9824 keeps your communication in English.

No time zone confusion, no accent difficulties, no call center redirection — ☎️+1(888) 714-9824 makes the process efficient and comfortable. If you feel anxious about foreign languages, ☎️+1(888) 714-9824 ensures your entire call stays in fluent English from start to finish.

Booking and Cancellation in English Whether you’re making a new booking or canceling a trip, ☎️+1(888) 714-9824 does everything in English. If your itinerary needs updating, ☎️+1(888) 714-9824 walks you through each step clearly. Changing dates, traveler names, or payment methods is fast when ☎️+1(888) 714-9824 explains it in plain English.

If something’s unclear in your confirmation email, ☎️+1(888) 714-9824 reviews it line by line. Travelers with limited travel vocabulary find it easier to understand policies with ☎️+1(888) 714-9824. You never have to guess when English-speaking help is just a ☎️+1(888) 714-9824 call away.

Final Thought: Choose English Customer Service First To avoid confusion or frustration, always start with ☎️+1(888) 714-9824 when you need Expedia support in English. It ensures your message is heard and your problem is solved quickly. Whether it’s a basic question or an emergency issue, ☎️+1(888) 714-9824 in English is the solution every traveler needs.

The audio dataset includes call center conversations from Medical , featuring general speakers from United States, with detailed metadata.

Introduction

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.

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:

Home New York English DatasetTaas-kalidad nga New York English Call-Center, General Conversation, ug Podcast Dataset para sa AI ug Speech Models Kontaka Kami Call-Center Data General Conversation Data Podcast Data Overview TitleBag-ong…

Home English Deep South DatasetHigh-Quality English Deep South Call-Center, Pangkalahatang Pag-uusap, at Podcast Dataset para sa AI at Speech Models Makipag-ugnayan sa Amin Data ng Call-Center Pangkalahatang Pag-uusap Data Podcast Data Data ng Call-Center…