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  <!This dataset card aims to be a base template for new datasets. It has been generated using [this raw template](https://github.com/huggingface/huggingface_hub/blob/main/src/huggingface_hub/templates/datasetcard_template.md?plain=1).>
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- IMPORTANT: This is the raw version of the LnNor corpus. If you intend to use the dataset for training or evaluation, you may be more interested in MultiBridge/LnNor, which contains the same audio recordings, but segmented into smaller samples and converted to mono at 16 kHz.
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  A multilingual dataset of high-quality speech recordings in Norwegian, English, and Polish, designed for research into cross-linguistic influence, multilingual language acquisition, and applications in NLP and speech processing such as ASR, TTS, and linguistic variability modeling. The dataset includes 2,783 recordings, totaling 101 hours, with a size of 50.1 GB. These recordings capture phonological, syntactic, and semantic variability through structured tasks like reading, picture description, and spontaneous conversation.
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  ## Dataset Details
 
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  <!This dataset card aims to be a base template for new datasets. It has been generated using [this raw template](https://github.com/huggingface/huggingface_hub/blob/main/src/huggingface_hub/templates/datasetcard_template.md?plain=1).>
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+ IMPORTANT: This is the raw version of the LnNor corpus. If you intend to use the dataset for training or evaluation, you may be more interested in [MultiBridge/LnNor](https://huggingface.co/datasets/MultiBridge/LnNor), which contains the same audio recordings, but segmented into smaller samples and converted to mono at 16 kHz.
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  A multilingual dataset of high-quality speech recordings in Norwegian, English, and Polish, designed for research into cross-linguistic influence, multilingual language acquisition, and applications in NLP and speech processing such as ASR, TTS, and linguistic variability modeling. The dataset includes 2,783 recordings, totaling 101 hours, with a size of 50.1 GB. These recordings capture phonological, syntactic, and semantic variability through structured tasks like reading, picture description, and spontaneous conversation.
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  ## Dataset Details