| --- |
| license: cc-by-nc-nd-4.0 |
| task_categories: |
| - automatic-speech-recognition |
| language: |
| - nl |
| tags: |
| - speech |
| - speech recognition |
| - audio |
| - machine |
| - machine learning |
| - dutch |
| size_categories: |
| - n<1K |
| --- |
| # 🎧 Dutch Speech Dataset |
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| The **Dutch Speech Dataset** is a high-quality **speech audio dataset** designed to provide structured and diverse **audio data** for modern AI and machine learning applications. It includes **179 hours of audio data** across **548 files**, delivered in **MP3 and WAV formats**, with a total size of **190 MB**. This well-organized **audio dataset** ensures balanced and representative **voice data**, with **51% female and 49% male speakers**, and a wide age distribution from **18 to 50+ years**. The **dataset language** is Dutch, covering speakers from the Netherlands, Belgium (Flanders), Suriname, Aruba, and Curaçao, making it a comprehensive **language speech dataset** with strong regional and phonetic diversity. |
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| 🔗 **Learn more:** |
| https://speech-data.ai/datasets/dutch/ |
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|
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| ## 🚀 Use Cases |
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| This **Dutch speech dataset** supports a wide range of AI applications, including **speech recognition**, voice assistant development, and natural language processing. The structured **speech data** enables efficient acoustic modeling, speaker identification, and scalable AI training workflows. It serves as a reliable **speech recognition dataset** for both research and production environments, ensuring consistent performance across dialects and recording conditions. |
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| ## 📊 Dataset Metadata |
|
|
| | Field | Value | |
| |------------------|-----------------------------------------------------------------------| |
| | 📜 License | CC BY-NC-ND 4.0 | |
| | 🎯 Task Categories | Automatic Speech Recognition | |
| | 🌍 Language | Dutch (nl) | |
| | 🏷️ Tags | Speech, Speech Recognition, Audio, Machine, Machine Learning, Dutch | |
| | 📦 Size Category | n < 1K | |
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| --- |
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| ## ⭐ Key Value |
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| The key value of this **speech dataset** lies in its geographic coverage, balanced speaker distribution, and production-ready structure. It delivers high-quality **audio data** that enhances the accuracy and robustness of AI systems in real-world multilingual environments. This **voice dataset** is ideal for building scalable and high-performance voice-enabled applications. |
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