Update README.md with data structure description
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README.md
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license:
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multilinguality:
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- monolingual
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dataset_info:
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---
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# MOCKS
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## Table of Contents
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- [Table of Contents](#table-of-contents)
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## Dataset Description
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- **Homepage:**
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- **Repository:**
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- **Paper:**
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- **Leaderboard:**
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- **Point of Contact:**
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### Dataset Summary
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Please refer to our [paper]() for further details.
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[More Information Needed - add link to paper]
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### Supported Tasks and Leaderboards
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The MOCKS dataset can be used for Open-Vocabulary Keyword Spotting (OV-KWS) task. It supports two OV-KWS types:
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## Dataset Structure
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- different examples - test examples with completaly different prases.
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## Dataset Creation
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The offline testset contains additional 0.1 second at the beginning and end of extracted audio sample to mitigate the cut-speech effect.
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The online version contrains additional 1 second or so at the beginning and end of extracted audio sample.
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[More Information Needed]
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### Source Data
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#### Initial Data Collection and Normalization
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[More Information Needed]
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#### Who are the source language producers?
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[More Information Needed]
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### Annotations
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#### Annotation process
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[More Information Needed]
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#### Who are the annotators?
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[More Information Needed]
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### Personal and Sensitive Information
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## Considerations for Using the Data
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### Social Impact of Dataset
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[More Information Needed]
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### Discussion of Biases
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The MOCKS testset is speaker gender balanced.
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### Other Known Limitations
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[More Information Needed]
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## Additional Information
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### Dataset Curators
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[More Information Needed]
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### Licensing Information
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### Citation Information
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```bibtex
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@inproceedings{pudo23_interspeech,
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year={in press.},
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booktitle={Proc. Interspeech 2023},
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}
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```
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### Contributions
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Thanks to [@github-username](https://github.com/<github-username>) for adding this dataset.
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- fr
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license:
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- cc-by-4.0
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- mpl-2.0
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multilinguality:
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- monolingual
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dataset_info:
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---
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# MOCKS: Multilingual Open Custom Keyword Spotting Testset
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## Table of Contents
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- [Table of Contents](#table-of-contents)
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## Dataset Description
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- **Paper:**
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### Dataset Summary
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Please refer to our [paper]() for further details.
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### Supported Tasks and Leaderboards
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The MOCKS dataset can be used for Open-Vocabulary Keyword Spotting (OV-KWS) task. It supports two OV-KWS types:
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## Dataset Structure
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The MOCKS testset is split by language, source dataset and OV-KWS type:
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```
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MOCKS
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│
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└───de
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│ └───MCV
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│ │ └───test
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│ │ │ └───offline
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│ │ │ │ │ all.pair.different.tsv
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│ │ │ │ │ all.pair.positive.tsv
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│ │ │ │ │ all.pair.similar.tsv
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│ │ │ │ │ data.tar.gz
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│ │ │ │ │ subset.pair.different.tsv
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│ │ │ │ │ subset.pair.positive.tsv
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│ │ │ │ │ subset.pair.similar.tsv
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│ │ │ │
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│ │ │ └───online
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│ │ │ │ │ all.pair.different.tsv
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│ │ │ │ │ ...
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│ │ │ │ data.offline.transcription.tsv
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│ │ │ │ data.online.transcription.tsv
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│
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└───en
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│ └───LS-clean
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│ │ └───test
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│ │ │ └───offline
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│ │ │ │ │ all.pair.different.tsv
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│ │ │ │ │ ...
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│ │ │ │ ...
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│ │
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│ └───LS-other
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│ │ └───test
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│ │ │ └───offline
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│ │ │ │ │ all.pair.different.tsv
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│ │ │ │ │ ...
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│ │ │ │ ...
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│ │
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│ └───MCV
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│ │ └───test
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│ │ │ └───offline
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│ │ │ │ │ all.pair.different.tsv
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│ │ │ │ │ ...
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│ │ │ │ ...
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│
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└───...
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```
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Each split is divided into:
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- positive examples (`all.pair.positive.tsv`) - test examples with true keyword, 5000-8000 keywords in each subset,
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- similar examples (`all.pair.similar.tsv`) - test examples with similar phrases to keyword selected based on phonetic transcription distance,
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- different examples (`all.pair.different.tsv`) - test examples with completaly different prases.
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All those files contain columns separated by tab:
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- `keyword_path` - path to audio containing keyword phrase.
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- `adversary_keyword_path` - path to test audio.
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- `adversary_keyword_timestamp_start` - start time in seconds of phrase of interest for given keyword from `keyword_path`, field only available in **offline** split.
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- `adversary_keyword_timestamp_end` - end time in seconds of phrase of interest for given keyword from `keyword_path`, field only available in **offline** split.
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- `label` - whether the `adversary_keyword_path` contain keyword from `keyword_path` or not (1 - contains keyword, 0 - doesn't contain keyword).
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Each split also contains subset of whole data with the same field sctructure to allow faster evaluation (`subset.pair.*.tsv`).
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Also, trascriptions are provided for each audio in:
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- `data_offline_transcription.tsv` - transcriptions for **offline** examples and `keyword_path` from **online** scenario,
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- `data_online_transcription.tsv` - transcriptions for adversary, test examples from **online** scenario,
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three columns are present within each file:
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- `path_to_keyword`/`path_to_adversary_keyword` - path to audio file,
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- `keyword_transcription`/`adversary_keyword_transcription` - audio transcription,
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- `keyword_phonetic_transcription`/`adversary_keyword_phonetic_transcription` - audio phonetic transcription.
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## Dataset Creation
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The offline testset contains additional 0.1 second at the beginning and end of extracted audio sample to mitigate the cut-speech effect.
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The online version contrains additional 1 second or so at the beginning and end of extracted audio sample.
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The MOCKS testset is gender balanced.
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## Citation Information
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```bibtex
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@inproceedings{pudo23_interspeech,
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year={in press.},
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booktitle={Proc. Interspeech 2023},
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}
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```
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