Datasets:
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---
license: cc-by-sa-4.0
language:
- en
size_categories:
- 10M<n<100M
---
This is the dataset presented in my [ASRU-2023 paper](https://arxiv.org/abs/2309.17267).
It consists of multiple files:
Keys2Paragraphs.txt (internal name in scripts: yago_wiki.txt):
4.3 million unique words/phrases (English Wikipedia titles or their parts) occurring in 33.8 million English Wikipedia paragraphs.
Keys2Corruptions.txt (internal name in scripts: sub_misspells.txt):
26 million phrase pairs in the corrupted phrase inventory, as recognized by different ASR models
Keys2Related.txt (internal name in scripts: related_phrases.txt):
62.7 million phrase pairs in the related phrase inventory
FalsePositives.txt (internal name in scripts: false_positives.txt):
449 thousand phrase pairs in the false positive phrase inventory
NgramMappings.txt (internal name in scripts: replacement_vocab_filt.txt):
5.5 million character n-gram mappings dictionary
asr
outputs of g2p+tts+asr using 4 different ASR systems (conformer ctc was used twice),
gives pairs of initial phrase and its recognition result.
Does not include .wav files, but these can be reproduced by feeding g2p to tts
giza
raw outputs of GIZA++ alignments for each corpus,
from these we get NgramMappings.txt and Keys2Corruptions.txt
This [example code](https://github.com/bene-ges/nemo_compatible/blob/spellmapper_new_false_positive_sampling/scripts/nlp/en_spellmapper/dataset_preparation/build_training_data_from_wiki_en_asr_adapt.sh) shows how to generate training data from this dataset.
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