Bengali (Bangladesh) Real Life Conversational Data

Synthetic Data Generation

Tags and Keywords

Podcast

Bangladesh

Bengali

Conversational

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Bengali (Bangladesh) Real Life Conversational Data Dataset on Opendatabay data marketplace

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£6,000

About

High-Fidelity Bengali Conversational Speech Dataset

Description

This data product is a massive-scale, professionally curated collection of natural, spontaneous Bengali conversations designed specifically for training state-of-the-art Automatic Speech Recognition (ASR), Large Language Models (LLMs), and Voice Synthesis systems.
The dataset captures authentic daily-life interactions across diverse socioeconomic topics, providing the linguistic nuance, emotional prosody, and background acoustic variety necessary for "human-level" AI performance in the Bengali language.

Data Product Features

  • Dual-Channel (Diarized) Audio: Speakers are recorded on separate mono channels to ensure 100% accurate speaker diarization and overlap handling.
  • Spontaneous Dialogue: 100% unscripted speech covering real-world scenarios like inflation, professional development, and cultural discourse.
  • Standardized Labeling: High-accuracy time-stamped metadata for every conversational turn.
  • Acoustic Diversity: Recorded in varied environments to ensure model robustness against background noise.

Distribution

The dataset is structured for easy ingestion into high-performance computing (HPC) environments.
  • Data Volume: ~150,000 to 200,000 hours of valid speech.
  • Sample Format: .opus (Compressed OGG) provided for free preview and evaluation.
  • Premium Format: 48kHz / 24-bit .wav (Uncompressed PCM) available upon enterprise request.
  • Delivery: Direct S3-to-S3 transfer or secure physical drive delivery.

Usage

This data product is ideal for a variety of applications:
  • ASR Training: Building highly accurate speech-to-text systems for the Bengali language.
  • LLM Fine-Tuning: Extracting linguistic patterns and cultural context for Bengali generative AI.
  • Voice Biometrics: Training speaker identification systems using high-fidelity diarized channels.
  • Sentiment Analysis: Training models to recognize tone, urgency, and emotion in South Asian dialects.

Coverage

Explain the scope and coverage of the data product:
  • Geographic Coverage: Bangladesh (Multiple regional dialects represented).
  • Time Range: January 2024 - March 2026.
  • Demographics: Balanced representation across genders (Male/Female) and age groups (18–65), covering various urban and rural professional industries.

License

CUSTOM - Enterprise Data License

AI Training Rights

Licensee is granted a non-exclusive, worldwide, and perpetual right to:
  • Use the Data Product to train, fine-tune, and evaluate machine learning models, including large language models.
  • Incorporate Data Product content into models and commercialize resulting model outputs.
  • Create derivative works (model weights, embeddings, etc.) for any lawful purpose.
Restrictions:
  • The Data Product itself may not be sold, redistributed, or shared outside of licensed usage.
  • Licensee must comply with all applicable laws, including data protection and privacy regulations.

Who Can Use It

  • Data Scientists: For training and fine-tuning machine learning models.
  • AI Research Labs: For pushing the boundaries of low-resource language modeling.
  • Global Businesses: For localizing voice assistants and customer service bots for the 300M+ Bengali speakers.

Data Dictionary

| Column Name | Data Type | Description | Possible Values/Notes | | :--- | :--- | :--- | :--- | | audio_id | String | Unique identifier for the recording session. | UUID format | | duration_sec | Float | Total length of the valid audio in seconds. | e.g., 1800.50 | | channel_count | Integer | Number of audio channels. | 2 (Left: User A, Right: User B) | | topic_category | String | The primary subject of the conversation. | Economy, Education, Tech, etc. | | sampling_rate | Integer | Fidelity of the master recording. | 48000 (Hz) | | transcript_url | String | Path to the associated JSON/Text label. | S3 Path |

Additional Notes: While the .opus samples provided for free are sufficient for initial testing and quality verification, the full master set is maintained in lossless .wav format to ensure maximum feature extraction for deep learning.
For pricing, full dataset access, or custom data collection requests, please contact us

Listing Stats

VIEWS

14

DELIVERY

INSTANT DOWNLOAD

LISTED

05/04/2026

UPDATED

07/04/2026

REGION

ASIA

Universal Data Quality Score Logo UDQSQUALITY

5 / 5

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£6,000

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