Dutch (Netherlands) General Conversation Speech Dataset

The audio dataset consist of general conversations between native Dutch people from Netherlands along with metadata and transcription.


Unscripted General Conversations

Total Volume

50 Speech Hours

Last updated

July 2023

Number of participants


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About this Off-the-shelf Speech Dataset

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What’s Included

Welcome to the Dutch Language General Conversation Speech Dataset, a comprehensive and diverse collection of voice data specifically curated to advance the development of Dutch language speech recognition models, with a particular focus on Netherlands accents and dialects.

With high-quality audio recordings, detailed metadata, and accurate transcriptions, it empowers researchers and developers to enhance natural language processing, conversational AI, and Generative Voice AI algorithms. Moreover, it facilitates the creation of sophisticated voice assistants and voice bots tailored to the unique linguistic nuances found in the Dutch language spoken in Netherlands.

Speech Data:

This training dataset comprises 50 hours of audio recordings covering a wide range of topics and scenarios, ensuring robustness and accuracy in speech technology applications. To achieve this, we collaborated with a diverse network of 70 native Dutch speakers from different states/provinces of Netherlands. This collaborative effort guarantees a balanced representation of Netherlands accents, dialects, and demographics, reducing biases and promoting inclusivity.

Each audio recording captures the essence of spontaneous, unscripted conversations between two individuals, with an average duration ranging from 15 to 60 minutes. The speech data is available in WAV format, with stereo channel files having a bit depth of 16 bits and a sample rate of 8 kHz. The recording environment is generally quiet, without background noise and echo.


In addition to the audio recordings, our dataset provides comprehensive metadata for each participant. This metadata includes the participant's age, gender, country, state, and dialect. Furthermore, additional metadata such as recording device detail, topic of recording, bit depth, and sample rate will be provided.

The metadata serves as a valuable tool for understanding and characterizing the data, facilitating informed decision-making in the development of Dutch language speech recognition models.


This dataset provides a manual verbatim transcription of each audio file to enhance your workflow efficiency. The transcriptions are available in JSON format. The transcriptions capture speaker-wise transcription with time-coded segmentation along with non-speech labels and tags.

Our goal is to expedite the deployment of Dutch language conversational AI and NLP models by offering ready-to-use transcriptions, ultimately saving valuable time and resources in the development process.

Updates and Customization:

We understand the importance of collecting data in various environments to build robust ASR models. Therefore, our voice dataset is regularly updated with new audio data captured in diverse real-world conditions.

If you require a custom training dataset with specific environmental conditions such as in-car, busy street, restaurant, or any other scenario, we can accommodate your request. We can provide voice data with customized sample rates ranging from 8kHz to 48kHz, allowing you to fine-tune your models for different audio recording setups. Additionally, we can also customize the transcription following your specific guidelines and requirements, to further support your ASR development process.


This audio dataset, created by FutureBeeAI, is now available for commercial use.


Whether you are training or fine-tuning speech recognition models, advancing NLP algorithms, exploring generative voice AI, or building cutting-edge voice assistants and bots, our dataset serves as a reliable and valuable resource.

Use Cases

Use of speech data for Automatic Speech Recognition


Use of speech data in Conversational AI

Conversational AI

Use of speech data for Chatbot & voicebot creation


Use of speech data in Language Modeling

Language Modelling

Use of speech data in Text-into-speech


Speech data usecase in Speech Analytics

Speech Analytics

Dataset Sample(s)

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Samples will be available soon!

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Dataset Demographics

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Language code






Gender Distribution

M:55, F:45

Age Group


Audio File Details

Details Headline


Silent, Noisy

Bit Depth

16 bit



Sample rate



Dual separate channel

Audio file duration

15-60 minutes

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