| --- |
| license: cc-by-4.0 |
| dataset_info: |
| features: |
| - name: audio |
| dtype: audio |
| splits: |
| - name: train |
| num_bytes: 104882523 |
| num_examples: 10 |
| download_size: 96333545 |
| dataset_size: 104882523 |
| configs: |
| - config_name: default |
| data_files: |
| - split: train |
| path: data/train-* |
| size_categories: |
| - n<1K |
| language: |
| - ar |
| tags: |
| - Audio |
| - Podcast |
| - Arabic |
| - Clear |
| - Raw |
| - Benchmark |
| - Optimization |
| --- |
| **Dataset Description:** |
|
|
| This dataset is a **large-scale collection of raw Arabic podcast audio**, specifically designed to support the development and pretraining of speech and language models. |
|
|
| It captures real-world interactions across diverse topics and formats. The dataset preserves natural speech patterns, speaker variability, and authentic podcast environments, making it highly valuable for building robust, scalable, and production-ready AI systems. |
| Additionally, this dataset can be used in data pipelines for **Supervised Fine-Tuning (SFT) and Reinforcement Learning with Human Feedback (RLHF) workflows**. |
|
|
| **Key Use Cases** |
|
|
| -Pretraining Automatic Speech Recognition (ASR) systems |
| -Speech-to-Text (STT) systems |
| -Self-supervised learning (SSL) for speech models |
| -Large Language Models (LLMs) with audio understanding capabilities |
| -Speech representation learning |
| -Noise-robust and real-world voice applications |
| |
| **Dataset Specification** |
|
|
| -Language: Arabic |
| -Type: Raw, unprocessed podcast audio, Single Channel |
| -Speech Style: Natural, conversational, unscripted |
| -Audio Conditions: Real-world environments (including noise and variability) |
| -Domains: discussions, storytelling, interviews, etc. |
| -Format: .wav, .mp3, .ogg, etc. |
| -Sampling Rate: 8000 Hz |
| -Duration: 6024 hours |
| |
| **Value of Single Channel Dataset** |
|
|
| -Training models that can handle real-world conversational complexity |
| -Improved performance in noisy and uncontrolled environments |
| -Development of accurate speaker diarization systems |
| -Better generalization across accents, tones, and speaking styles |
| -flexible preprocessing and custom annotation pipelines tailored to specific business needs |
| |
| **Basic JSON Schema** |
| ```json |
| { |
| "id": "string", |
| "audio_filepath": "string", |
| "duration": "float", |
| "language": "string", |
| "sample_rate": "integer", |
| "format": "string", |
| "num_speakers": "integer", |
| "domain": "string", |
| "metadata": { |
| "source": "string", |
| "recording_condition": "string" |
| } |
| } |
| ``` |
|
|
| **Full Dataset Overview** |
|
|
| Total Duration (in hours): 57,568 |
|
|
| This dataset is part of a large multilingual podcast audio collection covering the following languages: |
| Arabic, Bengali, English, Gujarati, Hindi, Kannada, Malayalam, Marathi, Punjabi, Tamil, Telugu, and Urdu. |
|
|
| **Data Creation** |
|
|
| Procured through formal agreements and generated in the ordinary course of business. |
|
|
| **Considerations** |
|
|
| This dataset is provided for research and educational purposes only. It contains only sample data. For access to the full dataset and enterprise licensing options, please visit our website[InfoBay AI](https://infobay.ai/) or contact us directly. |
|
|
| -Ph: (91) 8303174762 |
| -Email: vipul@infobay.ai |
