Datasets:
Tasks:
Automatic Speech Recognition
Formats:
parquet
Languages:
English
Size:
100K - 1M
ArXiv:
License:
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 | |
``` |