
This is the training dataset used to train the first version of the SpellMapper model.
It consists of 33'547'074 training examples.
Actually, [this checkpoint](https://huggingface.co/bene-ges/spellmapper_asr_customization_en) was trained only 1/3 of the full dataset.

Paper: [SpellMapper: A non-autoregressive neural spellchecker for ASR customization with candidate retrieval based on n-gram mappings](https://arxiv.org/abs/2306.02317)

## Citation

```bibtex
   @inproceedings{inproceedings,
      author = {Antonova, Alexandra and Bakhturina, Evelina and Ginsburg, Boris},
      year = {2023},
      month = {08},
      pages = {1404-1408},
      title = {SpellMapper: A non-autoregressive neural spellchecker for ASR customization with candidate retrieval based on n-gram mappings},
      doi = {10.21437/Interspeech.2023-768}
   }
```
task_categories:token-classification size_categories:10M<n<100M language:en license:cc-by-4.0 arxiv:2306.02317 region:us
{"language": ["en"], "license": "cc-by-4.0", "size_categories": ["10M<n<100M"], "task_categories": ["token-classification"]}
TAGS
#task_categories-token-classification #size_categories-10M<n<100M #language-English #license-cc-by-4.0 #arxiv-2306.02317 #region-us 


This is the training dataset used to train the first version of the SpellMapper model.
It consists of 33'547'074 training examples.
Actually, this checkpoint was trained only 1/3 of the full dataset.

Paper: SpellMapper: A non-autoregressive neural spellchecker for ASR customization with candidate retrieval based on n-gram mappings


TAGS
#task_categories-token-classification #size_categories-10M<n<100M #language-English #license-cc-by-4.0 #arxiv-2306.02317 #region-us 
