keyword
stringclasses
618 values
audio
audioduration (s)
0.97
1
translation
stringclasses
537 values
abhaile
home
abhaile
home
abhaile
home
abhainn
river
abhainn
river
abhainn
river
abhainn
river
abhainn
river
abhainn
river
ach
but
ach
but
ach
but
ach
but
ach
but
ach
but
ach
but
ach
but
ach
but
ach
but
ach
but
ach
but
ach
but
ach
but
ach
but
ach
but
ach
but
ach
but
ach
but
ach
but
ach
but
ach
but
ach
but
ach
but
ach
but
ach
but
ach
but
ach
but
ach
but
ach
but
ach
but
ach
but
ach
but
ach
but
ach
but
ach
but
ach
but
ach
but
ach
but
ach
but
ach
but
ach
but
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but
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but
ach
but
ach
but
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but
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but
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but
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but
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but
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but
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but
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but
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but
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but
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but
ach
but
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but
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but
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but
ach
but
ach
but
ach
but
ach
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but
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achomhairc
appeals
achomhairc
appeals
achomhairc
appeals
achomhairc
appeals
achomhairc
appeals
achomhairc
appeals
achomhairc
appeals
acht
act
acht
act
acht
act
acht
act
acht
act
acht
act
acht
act
acht
act
acht
act
acht
act
acmhainn
resource
acmhainn
resource
acmhainn
resource

Dataset Card for Dataset Name

This is the Irish portion of the Spoken Words dataset (available at MLCommons/ml_spoken_words), with merged splits “train”, “validation”, and “test”, augmented with machine translation. The Irish sentences are automatically translated into English using Google Translation API. The dataset includes approximately 3 hours and 2 minutes of audio (03:02:02), spoken by multiple narrators.

Dataset Structure

Dataset({
    features: ['keyword', 'audio', 'translation'],
    num_rows: 10925
})

How to load the dataset

from datasets import load_dataset

dataset = load_dataset("SpokenWords-GA-EN-MTed",
                       split="train",
                       trust_remote_code=True
                      )

Citations

@inproceedings{mazumder2021multilingual,
  title={Multilingual Spoken Words Corpus},
  author={Mazumder, Mark and Chitlangia, Sharad and Banbury, Colby and Kang, Yiping and Ciro, Juan Manuel and Achorn, Keith and Galvez, Daniel and Sabini, Mark and Mattson, Peter and Kanter, David and others},
  booktitle={Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2)},
  year={2021}
}
@inproceedings{moslem2024leveraging,
  title={Leveraging Synthetic Audio Data for End-to-End Low-Resource Speech Translation},
  author={Moslem, Yasmin},
  booktitle={Proceedings of the 2024 International Conference on Spoken Language Translation (IWSLT 2024)},
  year={2024},
  month={April}
}
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