Saudi Arabian Scripted Monologue Speech Dataset for Telecom Domain

The audio dataset comprises scripted monologue speech data in the Telecom domain, featuring native Arabic speakers from Saudi. It includes speech data, detailed metadata, and accurate transcriptions.

About this Off-the-shelf Speech Dataset

Introduction

Presenting the Saudi Arabian Arabic Scripted Monologue Speech Dataset for the Telecom Domain, a purpose-built dataset created to accelerate the development of Arabic speech recognition and voice AI models specifically tailored for the telecommunications industry.

Speech Data

This dataset includes over 6,000 high-quality scripted prompt recordings in Saudi Arabian Arabic, representing real-world telecom customer service scenarios. It’s designed to support the training of speech-based AI systems used in call centers, virtual agents, and voice-powered support tools.

•Participant Diversity

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Speakers: 60 native Saudi Arabian Arabic speakers

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Geographic Distribution: Carefully selected from multiple regions across Saudi Arabia to capture a wide spectrum of dialects and speaking styles

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Demographics: Balanced representation of males and females (60:40 ratio), aged between 18 to 70 years

•Recording Specifications

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Type: Scripted monologue prompts focused on telecom industry use cases

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Duration: Each audio clip ranges from 5 to 30 seconds

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Format: WAV files in mono, 16-bit depth, with sample rates of 8 kHz and 16 kHz

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Environment: Clean, echo-free, and noise-controlled settings to ensure optimal audio clarity

Topic Coverage

The dataset reflects a wide variety of common telecom customer interactions, including:

•Customer onboarding and service inquiries

•Billing and payment questions

•Data plans and product information

•Technical support requests

•Network coverage discussions

•Regulatory compliance and policy information

•Upgrades, renewals, and service plan changes

•Domain-specific scripted interactions tailored to real-world telecom use cases

Contextual Depth

To maximize contextual richness, prompts include:

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Localized Names: Common Saudi Arabia names in various formats

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Addresses: Region-specific address structures for realism

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Dates & Times: Spoken date and time references in typical telecom scenarios (e.g., billing cycles, service activation times)

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Telecom Terminology: Keywords related to mobile data, network, SIM, devices, plans, etc.

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Numbers & Rates: Usage statistics, pricing info, recharge values, and billing figures

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Service Providers: References to telecom companies and third-party service entities

Transcription

Each audio file is paired with an accurate, verbatim transcription for precise model training:

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Content: Transcriptions are direct representations of each recorded prompt

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Format: Plain text (.TXT), with filenames matching their corresponding audio files

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Verification: Every transcription is manually verified by native Saudi Arabian Arabic linguists to ensure consistency and accuracy

Metadata

Detailed metadata is included to enhance dataset usability and traceability:

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Participant Metadata: Unique speaker ID, age, gender, country, state, dialect

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Audio Metadata: Text transcript, recording conditions, device used

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Audio specifications: Format, sample rate, bit depth

This metadata provides deep insight into speaker profiles and recording context, ideal for nuanced model training and analysis.

Use Cases & Applications

This dataset is suitable for a wide range of telecom-centric AI use cases:

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Automatic Speech Recognition (ASR): Train domain-specific ASR models in Saudi Arabian Arabic

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Voice Synthesis (TTS): Generate synthetic telecom voices using diverse speech samples

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Voice Assistants: Build natural-sounding telecom virtual agents and IVR systems

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Conversational AI & Chatbots: Train customer service chatbots to handle voice-to-text and NLP interactions

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NER & Intent Recognition: Identify telecom-specific entities like plan types, billing details, and account references

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Sentiment Analysis & Language Understanding: Perform domain-focused sentiment classification and semantic comprehension

Secure & Ethical Data Collection

All data was collected using FutureBeeAI’s proprietary platform, Yugo, with full participant consent.

•Recordings were conducted in a secure, monitored environment, adhering to stringent privacy protocols.

•No personally identifiable information (PII) is included, ensuring the dataset is safe and compliant for commercial use.

License

The Saudi Arabian Arabic Scripted Monologue Speech Dataset for the Telecom Domain is available under a commercial use license, empowering you to build high-performance speech AI products across telecom applications.