https://github.com/amazon-science/real-world-noisy-benchmarks-for-natural-language-understanding
Benchmark test sets for real-world noise phenomena in goal-directed conversations in English.
https://github.com/amazon-science/real-world-noisy-benchmarks-for-natural-language-understanding
Science Score: 26.0%
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○CITATION.cff file
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○.zenodo.json file
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Found 1 DOI reference(s) in README -
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Low similarity (7.0%) to scientific vocabulary
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Benchmark test sets for real-world noise phenomena in goal-directed conversations in English.
Basic Info
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- Stars: 3
- Watchers: 8
- Forks: 1
- Open Issues: 0
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Metadata Files
README.md
Real World Noise Benchmarks for Natural Language Understanding
Project
If you use this dataset, please cite the following paper:
@inproceedings{sengupta-etal-2021-robustness,
title = "On the Robustness of Intent Classification and Slot Labeling in Goal-oriented Dialog Systems to Real-world Noise",
author = "Sengupta, Sailik and
Krone, Jason and
Mansour, Saab",
booktitle = "Proceedings of the 3rd Workshop on Natural Language Processing for Conversational AI",
month = nov,
year = "2021",
address = "Online",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2021.nlp4convai-1.7",
doi = "10.18653/v1/2021.nlp4convai-1.7",
pages = "68--79"
}
The directory structure is as follows:
- data
- atis
- abbreviations
- treatment_test.tsv
- allcaps
- treatment_test.tsv
- misspellings
- treatment_test.tsv
- morphological
- treatment_test.tsv
- paraphrase
- treatment_test.tsv
- punctuation
- treatment_test.tsv
- synonyms
- treatment_test.tsv
- snips
- abbreviations
- treatment_test.tsv
- allcaps
- treatment_test.tsv
- misspellings
- treatment_test.tsv
- morphological
- treatment_test.tsv
- paraphrase
- treatment_test.tsv
- synonyms
- treatment_test.tsv
Security
See CONTRIBUTING for more information.
License Summary
The documentation is made available under the Creative Commons Attribution-NonCommercial 4.0 International License. See the LICENSE file.
Owner
- Name: Amazon Science
- Login: amazon-science
- Kind: organization
- Website: https://amazon.science
- Twitter: AmazonScience
- Repositories: 80
- Profile: https://github.com/amazon-science
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