buckeye_asr / README.md
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Fix language and license tag names and tags (#2)
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---
annotations_creators:
- expert-generated
language_creators:
- crowdsourced
language:
- en
language_bcp47:
- en-US
license:
- other
multilinguality:
- monolingual
pretty_name: Buckeye Corpus
size_categories:
- unknown
source_datasets:
- original
task_categories:
- automatic-speech-recognition
task_ids:
- speech-recognition
---
# Dataset Card for the Buckeye Corpus (buckeye_asr)
## Table of Contents
- [Dataset Description](#dataset-description)
- [Dataset Summary](#dataset-summary)
- [Supported Tasks](#supported-tasks-and-leaderboards)
- [Languages](#languages)
- [Dataset Structure](#dataset-structure)
- [Data Instances](#data-instances)
- [Data Fields](#data-instances)
- [Data Splits](#data-instances)
- [Dataset Creation](#dataset-creation)
- [Curation Rationale](#curation-rationale)
- [Source Data](#source-data)
- [Annotations](#annotations)
- [Personal and Sensitive Information](#personal-and-sensitive-information)
- [Considerations for Using the Data](#considerations-for-using-the-data)
- [Social Impact of Dataset](#social-impact-of-dataset)
- [Discussion of Biases](#discussion-of-biases)
- [Other Known Limitations](#other-known-limitations)
- [Additional Information](#additional-information)
- [Dataset Curators](#dataset-curators)
- [Licensing Information](#licensing-information)
- [Citation Information](#citation-information)
## Dataset Description
- **Homepage:** https://buckeyecorpus.osu.edu/
- **Repository:** [Needs More Information]
- **Paper:** [Needs More Information]
- **Leaderboard:** [Needs More Information]
- **Point of Contact:** [Needs More Information]
### Dataset Summary
The Buckeye Corpus of conversational speech contains high-quality recordings from 40 speakers in Columbus OH conversing freely with an interviewer. The speech has been orthographically transcribed and phonetically labeled.
### Supported Tasks and Leaderboards
[Needs More Information]
### Languages
American English (en-US)
## Dataset Structure
### Data Instances
[Needs More Information]
### Data Fields
- `file`: filename of the audio file containing the utterance.
- `audio`: filename of the audio file containing the utterance.
- `text`: transcription of the utterance.
- `phonetic_detail`: list of phonetic annotations for the utterance (start, stop and label of each phone).
- `word_detail`: list of word annotations for the utterance (start, stop, label, broad and narrow transcriptions, syntactic class).
- `speaker_id`: string identifying the speaker.
- `id`: string identifying the utterance.
### Data Splits
The data is split in training, validation and test sets with different speakers (32, 4, and 4 speakers respectively) in each set. The sets are all balanced for speaker's gender and age.
## Dataset Creation
### Curation Rationale
[Needs More Information]
### Source Data
#### Initial Data Collection and Normalization
[Needs More Information]
#### Who are the source language producers?
[Needs More Information]
### Annotations
#### Annotation process
[Needs More Information]
#### Who are the annotators?
[Needs More Information]
### Personal and Sensitive Information
[Needs More Information]
## Considerations for Using the Data
### Social Impact of Dataset
[Needs More Information]
### Discussion of Biases
[Needs More Information]
### Other Known Limitations
[Needs More Information]
## Additional Information
### Dataset Curators
[Needs More Information]
### Licensing Information
FREE for noncommercial uses.
### Citation Information
```
@misc{pitt2007Buckeye,
title = {Buckeye {Corpus} of {Conversational} {Speech} (2nd release).},
url = {www.buckeyecorpus.osu.edu},
publisher = {Columbus, OH: Department of Psychology, Ohio State University (Distributor)},
author = {Pitt, M.A. and Dilley, L. and Johnson, K. and Kiesling, S. and Raymond, W. and Hume, E. and Fosler-Lussier, E.},
year = {2007},
}
```
### Usage
The first step is to download a copy of the dataset from [the official website](https://buckeyecorpus.osu.edu). Once done, the dataset can be loaded directly through the `datasets` library by running:
```
from datasets import load_dataset
dataset = load_dataset("bhigy/buckeye_asr", data_dir=<path_to_the_dataset>)
```
where `<path_to_the_dataset>` points to the folder where the dataset is stored. An example of path to one of the audio files is then `<path_to_the_dataset>/s01/s0101a.wav`.