Datasets:
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README.md
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- automatic-speech-recognition
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language:
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- en
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license:
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- cc-by-nc-sa-4.0
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- **Homepage:** [UWB-ATCC corpus homepage](https://lindat.mff.cuni.cz/repository/xmlui/handle/11858/00-097C-0000-0001-CCA1-0)
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- **Repository:** [GitHub repository (used in research)](https://github.com/idiap/w2v2-air-traffic)
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- **Paper:** [Air traffic control communication (ATCC) speech corpora and their use for ASR and TTS development](https://link.springer.com/article/10.1007/s10579-019-09449-5)
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### Dataset Summary
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- automatic-speech-recognition
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language:
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- en
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multilinguality:
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- monolingual
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license:
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- cc-by-nc-sa-4.0
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---
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- **Homepage:** [UWB-ATCC corpus homepage](https://lindat.mff.cuni.cz/repository/xmlui/handle/11858/00-097C-0000-0001-CCA1-0)
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- **Repository:** [GitHub repository (used in research)](https://github.com/idiap/w2v2-air-traffic)
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- **Paper:** [Air traffic control communication (ATCC) speech corpora and their use for ASR and TTS development](https://link.springer.com/article/10.1007/s10579-019-09449-5)
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- **Paper of this research:** [How Does Pre-trained Wav2Vec 2.0 Perform on Domain Shifted ASR? An Extensive Benchmark on Air Traffic Control Communications](https://arxiv.org/abs/2203.16822)
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### Dataset Summary
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