license: cc-by-4.0
task_categories:
- token-classification
language:
- en
size_categories:
- 100K<n<1M
tags:
- education
Dataset Card for Running Records Errors Dataset
Dataset Description
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Dataset Summary
The Running Records Errors dataset is an English-language dataset containing 1,055,601 sentences based on the Europarl corpus. As described in our paper, we take the sentences from the English version of the Europarl corpus and randomly inject three types of errors into the sentences: repetitions, where certain words or phrases are repeated, substitutions, where certain words are replaced with a different word, and deletions, where the word is completely omitted. The sentences are then passed into a TTS pipeline consisting of TacoTron2 and HifiGAN model to produce audio recordings of those mutated sentences. Lastly, the data is passed into a Quartznet 15x5 model which produces a transcript of the spoken audio.
Supported Tasks and Leaderboards
The original purpose of this dataset was to construct a model pipeline that could score running records assesments given a transcript of a child's speech along with the true text for that assesment. However, we provide this dataset to support other tasks involving error detection in text.
Languages
All of the data in the dataset is in English.
Dataset Structure
Data Instances
For each instance, there is a string for the audio transcript, a string for the original text before we added any errors, as well as a string of the sentence with the errors we generated. In addition, we provide two lists. One list denotes the original position of each word in the mutated text, and the second list denotes the error applied to that word.
Data Fields
- asr_transcript: The transcript of the audio processed by our Quartznet 15x5 model.
- original_text: The original text that was in the Europarl corupus. This text contains no artificial errors.
- mutated_text: This text contains the errors we injected.
- index_tags: This list denotes the original position of each word in
mutated_text. - mutated_tags: This list denotes the error applied to each word in
mutated_text.
Data Splits
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Dataset Creation
Curation Rationale
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Source Data
Initial Data Collection and Normalization
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Who are the source language producers?
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Annotations
Annotation process
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Who are the annotators?
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Personal and Sensitive Information
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Considerations for Using the Data
Social Impact of Dataset
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Discussion of Biases
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Other Known Limitations
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Additional Information
Dataset Curators
This dataset was generated with the guidance of @cehrett
Licensing Information
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Citation Information
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Contributions
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