Speech-data/bengali-speech-dataset

---
license: cc-by-nc-nd-4.0
task_categories:
- automatic-speech-recognition
tags:
- speech
- bengali
- audio
- speech recognition
- machine
- machine learning
language:
- bn
size_categories:
- n<1K
---
# 🎧 Bengali Speech Dataset

The **Bengali Speech Dataset** is a high-quality **speech audio dataset** designed to support advanced AI and machine learning systems with reliable **audio data**. It provides structured **voice data** for building and evaluating modern speech technologies, including conversational AI and multilingual models. The dataset contains **156 hours of audio data** across **643 files**, delivered in **MP3 and WAV formats**, with a total size of **285 MB**, making it a scalable resource for research and production environments.

This well-balanced **audio dataset** includes **52% female and 48% male speakers**, with age distribution ranging from 18 to 50+ years. The **dataset language** is Bengali, offering natural linguistic variation across speakers and accents. This makes it a robust **voice dataset** suitable for developing diverse **speech data** applications. It is structured to ensure clean segmentation and high-quality recordings, making it an effective **speech recognition dataset** for modern AI pipelines.

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🔗 **Learn more:**
https://speech-data.ai/datasets/bengali/

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## 🚀 Use Cases

This **Bengali speech dataset** is widely applicable in **speech recognition**, conversational AI systems, voice biometrics, and accent detection. It also supports language model training, phonetic research, and text-to-speech synthesis. The structured **speech audio dataset** enables efficient preprocessing and model training for both academic and industrial AI use cases.

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## ⭐ Key Value

The primary value of this **speech dataset** lies in its linguistic diversity, balanced speaker representation, and production-ready structure. It provides high-quality **audio data** that enhances the performance of AI systems in real-world multilingual environments. This **voice dataset** is especially valuable for building scalable and accurate speech-based technologies.