Urdu General Conversation Speech Dataset

This dataset captures real-world, unscripted conversations between native Urdu speakers. It includes detailed metadata and high-quality manual transcriptions, making it ideal for building accurate, human-like speech recognition and conversational AI systems.

Category

Unscripted General Conversations

Total Volume

60 Speech Hours

Last updated

June 2025

Number of participants

80

Urdu Pakistan speech dataset for ML and ASR training

About this Off-the-shelf Speech Dataset

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Introduction

Welcome to the Urdu General Conversation Speech Dataset — a rich, linguistically diverse corpus purpose-built to accelerate the development of Urdu speech technologies. This dataset is designed to train and fine-tune ASR systems, spoken language understanding models, and generative voice AI tailored to real-world Urdu communication.

Curated by FutureBeeAI, this 30 hours dataset offers unscripted, spontaneous two-speaker conversations across a wide array of real-life topics. It enables researchers, AI developers, and voice-first product teams to build robust, production-grade Urdu speech models that understand and respond to authentic Urdu accents and dialects.

Speech Data

The dataset comprises 30 hours of high-quality audio, featuring natural, free-flowing dialogue between native speakers of Urdu. These sessions range from informal daily talks to deeper, topic-specific discussions, ensuring variability and context richness for diverse use cases.

  • •Participant Diversity:
  • •
    Speakers: 60 verified native Urdu speakers from FutureBeeAI’s contributor community.
  • •
    Regions: Representing various provinces of Pakistan to ensure dialectal diversity and demographic balance.
  • •
    Demographics: A balanced gender ratio (60% male, 40% female) with participant ages ranging from 18 to 70 years.
  • •Recording Details:
  • •
    Conversation Style: Unscripted, spontaneous peer-to-peer dialogues.
  • •
    Duration: Each conversation ranges from 15 to 60 minutes.
  • •
    Audio Format: Stereo WAV files, 16-bit depth, recorded at 16kHz sample rate.
  • •
    Environment: Quiet, echo-free settings with no background noise.

    • Topic Diversity

    The dataset spans a wide variety of everyday and domain-relevant themes. This topic diversity ensures the resulting models are adaptable to broad speech contexts.

  • •Sample Topics Include:
  • •Family & Relationships
  • •Food & Recipes
  • •Education & Career
  • •Healthcare Discussions
  • •Social Issues
  • •Technology & Gadgets
  • •Travel & Local Culture
  • •Shopping & Marketplace Experiences, and many more.

    • Transcription

    Each audio file is paired with a human-verified, verbatim transcription available in JSON format.

  • •Transcription Highlights:
  • •Speaker-segmented dialogues
  • •Time-coded utterances
  • •Non-speech elements (pauses, laughter, etc.)
  • •High transcription accuracy, achieved through double QA pass, average WER < 5%

    • These transcriptions are production-ready, enabling seamless integration into ASR model pipelines or conversational AI workflows.

    Metadata

    The dataset comes with granular metadata for both speakers and recordings:

  • •
    Speaker Metadata: Age, gender, accent, dialect, state/province, and participant ID.
  • •
    Recording Metadata: Topic, duration, audio format, device type, and sample rate.

    • Such metadata helps developers fine-tune model training and supports use-case-specific filtering or demographic analysis.

    Usage and Applications

    This dataset is a versatile resource for multiple Urdu speech and language AI applications:

  • •
    ASR Development: Train accurate speech-to-text systems for Urdu.
  • •
    Voice Assistants: Build smart assistants capable of understanding natural Urdu conversations.
  • •
    Conversational AI: Develop chatbots and voicebots for multilingual or dialectal Urdu audiences.
  • •
    Speech Analytics: Extract patterns, detect topics, and evaluate speaker behavior.
  • •
    Generative Voice AI: Enable real-life dialogue synthesis or summarization with native-sounding output.

    • Secure and Ethical Collection

  • •All data was collected using “Yugo,” FutureBeeAI’s proprietary collection and transcription platform.
  • •Data remained within a secure environment throughout the process.
  • •Collected in compliance with strict privacy, consent, and ethical guidelines.
  • •No personally identifiable information is included in any recording or transcript.
  • •Free of copyrighted content. Safe for commercial and research use.

    • Customization and Updates

    We continuously enrich this dataset with new, naturally captured conversations. Additionally, we support project-specific data customization:

  • •Available Customization:
  • •
    Acoustic Conditions: In-car, restaurant, outdoor, or noisy environments on request.
  • •
    Sampling Rate: Custom WAV files at 8kHz to 48kHz.
  • •
    Transcription Guidelines: Tailored formatting, annotation levels, or QA standards.

    • License

    This Urdu General Conversation Dataset is created by FutureBeeAI and is available for commercial licensing.

    Use Cases

    Use of speech data for Automatic Speech Recognition

    ASR

    Use of speech data in Conversational AI

    Conversational AI

    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.

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    Dataset Details

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    Language

    Urdu

    Language code

    ur

    Country

    Pakistan

    Accents

    Dakhni, Dhakaiya ...more

    Gender Distribution

    M:55, F:45

    Age Group

    18-70 Years

    File Details

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    Environment

    Silent, Noisy

    Bit Depth

    16 bit

    Format

    wav

    Sample rate

    16khz

    Channel

    Stereo (dual-channel, separated speakers)

    Audio file duration

    15-60 minutes

    Read the License Terms
    Browse FAQs

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