Saudi Arabian Call Center Speech Dataset for Telecom

This Saudi Arabian speech dataset features real-world call center conversations from the Telecom domain. With detailed metadata and accurate transcriptions, it’s designed to power ASR systems, voice AI, and conversational agents.

Category

Unscripted Call Center Conversations

Total Volume

40 Speech Hours

Last updated

June 2025

Number of participants

80

Arabic (Saudi Arabia) call center speech data for voicebot

About this Off-the-shelf Speech Dataset

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Introduction

This Saudi Arabian Arabic 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 Arabic-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 Saudi Arabian Arabic 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: 80 native Saudi Arabian Arabic speakers from our verified contributor pool.
  • •
    Regions: Representing multiple provinces across Saudi Arabia 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 more

    • 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.

  • •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.
  • •
    Conversation Metadata: Topic, sentiment, call type, sample rate, and technical specs.

    • This metadata supports fine-grained analysis, dialect-specific tuning, and precise dataset segmentation.

    Usage and Applications

    This dataset is ideal for a range of telecom AI and NLP applications:

  • •
    Automatic Speech Recognition (ASR): Fine-tune Arabic speech-to-text systems for telecom interactions.
  • •
    Speech Analytics: Identify user pain points and improve telecom service delivery.
  • •
    Voice Assistants & Chatbots: Build telecom virtual assistants for customer self-service.
  • •
    Sentiment Analysis: Detect customer frustration or satisfaction in support calls.
  • •
    Generative AI: Train telecom-specific summarization and response generation models.

    • Secure and Ethical Collection

  • •All data was collected using “Yugo,” FutureBeeAI’s proprietary platform under strict ethical and security standards.
  • •No personally identifiable information is included.
  • • The Dataset complies with global data privacy guidelines and is copyright-free.

    • Updates and Customization

    We regularly expand this dataset with new telecom voice data and support full customization:

  • •Customization Options:
  • •
    Acoustic Environment: Silent or noisy upon request.
  • •
    Sample Rate: Customizable from 8kHz to 48kHz.
  • •
    Transcription Format: Can follow your QA and formatting requirements.

    • License

    This Telecom domain dataset is commercially licensed and ready for integration into Arabic ASR, NLP, and voice AI solutions.

    Use Cases

    Use of speech data in Conversational AI

    Call Center Conversational AI

    Use of speech data for Automatic Speech Recognition

    ASR

    Use of speech data for Chatbot & voicebot creation

    Chatbot

    Use of speech data in Language Modeling

    Language Modelling

    Use of speech data in Text-into-speech

    TTS

    Speech data usecase in Speech Analytics

    Speech Analytics

    Dataset Sample(s)

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    Samples will be available soon!

    Contact us to get the samples immediately for this dataset.

    Audio Promp 2 Bg

    Dataset Details

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    Language

    Arabic

    Language code

    ar-sa

    Country

    Saudi Arabia

    Gender Distribution

    M:60, F:40

    Age Group

    18-70 Years

    File Details

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    Environment

    Silent, Noisy

    Bit Depth

    16 bit

    Format

    wav

    Sample rate

    8khz & 16khz

    Channel

    Stereo (dual-channel, separated speakers)

    Audio file duration

    5-15 minutes

    Read the License Terms
    Browse FAQs

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