Datasets:
Tasks:
Automatic Speech Recognition
Formats:
parquet
Languages:
English
Size:
100K - 1M
ArXiv:
License:
File size: 5,115 Bytes
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---
dataset_info:
features:
- name: sex
dtype: string
- name: subset
dtype: string
- name: id
dtype: string
- name: audio
dtype: audio
- name: transcript
dtype: string
- name: words
list:
- name: end
dtype: float64
- name: start
dtype: float64
- name: word
dtype: string
- name: phonemes
list:
- name: end
dtype: float64
- name: phoneme
dtype: string
- name: start
dtype: float64
splits:
- name: dev_clean
num_bytes: 365310608.879
num_examples: 2703
- name: dev_other
num_bytes: 341143993.784
num_examples: 2864
- name: test_clean
num_bytes: 377535532.98
num_examples: 2620
- name: test_other
num_bytes: 351207892.569557
num_examples: 2938
- name: train_clean_100
num_bytes: 6694747231.610863
num_examples: 28538
- name: train_clean_360
num_bytes: 24163659711.787865
num_examples: 104008
- name: train_other_500
num_bytes: 32945085271.89443
num_examples: 148645
download_size: 62101682957
dataset_size: 65238690243.50571
configs:
- config_name: default
data_files:
- split: dev_clean
path: data/dev_clean-*
- split: dev_other
path: data/dev_other-*
- split: test_clean
path: data/test_clean-*
- split: test_other
path: data/test_other-*
- split: train_clean_100
path: data/train_clean_100-*
- split: train_clean_360
path: data/train_clean_360-*
- split: train_other_500
path: data/train_other_500-*
license: cc-by-4.0
task_categories:
- automatic-speech-recognition
language:
- en
pretty_name: Librispeech Alignments
size_categories:
- 100K<n<1M
---
# Dataset Card for Librispeech Alignments
Librispeech with alignments generated by the [Montreal Forced Aligner](https://montreal-forced-aligner.readthedocs.io/en/latest/). The original alignments in TextGrid format can be found [here](https://zenodo.org/records/2619474)
## Dataset Details
### Dataset Description
Librispeech is a corpus of read English speech, designed for training and evaluating automatic speech recognition (ASR) systems. The dataset contains 1000 hours of 16kHz read English speech derived from audiobooks.
The Montreal Forced Aligner (MFA) was used to generate word and phoneme level alignments for the Librispeech dataset.
- **Curated by:** Vassil Panayotov, Guoguo Chen, Daniel Povey, Sanjeev Khudanpur
- **Funded by:** DARPA LORELEI
- **Shared by:** Loren Lugosch
- **Language(s) (NLP):** English
- **License:** Creative Commons Attribution 4.0 International License
### Dataset Sources
- **Repository:** https://www.openslr.org/12
- **Paper:** https://arxiv.org/abs/1512.02595
- **Alignments:** https://zenodo.org/record/2619474
## Uses
### Direct Use
The Librispeech dataset can be used to train and evaluate ASR systems. The alignments allow for forced alignment techniques.
### Out-of-Scope Use
The dataset only contains read speech, so may not perform as well on spontaneous conversational speech.
## Dataset Structure
The dataset contains 1000 hours of segmented read English speech from audiobooks. There are three subsets: 100 hours (train-clean-100), 360 hours (train-clean-360) and 500 hours (train-other-500).
The alignments connect the audio to the reference text transcripts on word and phoneme level.
## Dataset Creation
### Curation Rationale
Librispeech was created to further speech recognition research and to benchmark progress in the field.
### Source Data
#### Data Collection and Processing
The audio and reference texts were sourced from read English audiobooks in the LibriVox project. The data was segmented, filtered and prepared for speech recognition.
#### Who are the source data producers?
The audiobooks are read by volunteers for the LibriVox project. Information about the readers is available in the LibriVox catalog.
### Annotations
#### Annotation process
The Montreal Forced Aligner was used to create word and phoneme level alignments between the audio and reference texts. The aligner is based on Kaldi.
#### Who are the annotators?
The alignments were generated automatically by the Montreal Forced Aligner and shared by Loren Lugosch.
#### Personal and Sensitive Information
The data contains read speech and transcripts. No personal or sensitive information expected.
## Bias, Risks, and Limitations
The dataset contains only read speech from published books, not natural conversational speech. Performance on other tasks may be reduced.
### Recommendations
Users should understand that the alignments may contain errors and account for this in applications.
## Citation
**BibTeX for Librispeech:**
```
@inproceedings{panayotov2015librispeech,
title={Librispeech: an ASR corpus based on public domain audio books},
author={Panayotov, Vassil and Chen, Guoguo and Povey, Daniel and Khudanpur, Sanjeev},
booktitle={ICASSP},
year={2015},
organization={IEEE}
}
```
**APA for Alignments:**
```
Lugosch, L. (2019). LibriSpeech Alignments (1.0) [Data set]. Zenodo. https://doi.org/10.5281/zenodo.2619474
``` |