Datasets:
pretty_name: MultiLingual LibriSpeech
annotations_creators:
- expert-generated
language_creators:
- crowdsourced
- expert-generated
language:
- de
- es
- fr
- it
- nl
- pl
- pt
license:
- cc-by-4.0
multilinguality:
- multilingual
paperswithcode_id: librispeech-1
size_categories:
- 100K<n<1M
source_datasets:
- original
task_categories:
- automatic-speech-recognition
- audio-classification
task_ids:
- speaker-identification
dataset_info:
- config_name: polish
features:
- name: file
dtype: string
- name: audio
dtype:
audio:
sampling_rate: 16000
- name: text
dtype: string
- name: speaker_id
dtype: int64
- name: chapter_id
dtype: int64
- name: id
dtype: string
splits:
- name: test
num_bytes: 332317
num_examples: 520
- name: train
num_bytes: 16136430
num_examples: 25043
- name: train.1h
num_bytes: 145411
num_examples: 238
- name: train.9h
num_bytes: 1383232
num_examples: 2173
- name: validation
num_bytes: 318964
num_examples: 512
download_size: 6609569551
dataset_size: 18316354
- config_name: german
features:
- name: file
dtype: string
- name: audio
dtype:
audio:
sampling_rate: 16000
- name: text
dtype: string
- name: speaker_id
dtype: int64
- name: chapter_id
dtype: int64
- name: id
dtype: string
splits:
- name: test
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num_examples: 3394
- name: train
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num_examples: 469942
- name: train.1h
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num_examples: 241
- name: train.9h
num_bytes: 1325460
num_examples: 2194
- name: validation
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num_examples: 3469
download_size: 122944886305
dataset_size: 282852748
- config_name: dutch
features:
- name: file
dtype: string
- name: audio
dtype:
audio:
sampling_rate: 16000
- name: text
dtype: string
- name: speaker_id
dtype: int64
- name: chapter_id
dtype: int64
- name: id
dtype: string
splits:
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num_examples: 3075
- name: train
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num_examples: 374287
- name: train.1h
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num_examples: 234
- name: train.9h
num_bytes: 1281951
num_examples: 2153
- name: validation
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num_examples: 3095
download_size: 92158429530
dataset_size: 224001789
- config_name: french
features:
- name: file
dtype: string
- name: audio
dtype:
audio:
sampling_rate: 16000
- name: text
dtype: string
- name: speaker_id
dtype: int64
- name: chapter_id
dtype: int64
- name: id
dtype: string
splits:
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num_examples: 2426
- name: train
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num_examples: 258213
- name: train.1h
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num_examples: 241
- name: train.9h
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num_examples: 2167
- name: validation
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num_examples: 2416
download_size: 64474642518
dataset_size: 166526210
- config_name: spanish
features:
- name: file
dtype: string
- name: audio
dtype:
audio:
sampling_rate: 16000
- name: text
dtype: string
- name: speaker_id
dtype: int64
- name: chapter_id
dtype: int64
- name: id
dtype: string
splits:
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num_examples: 2385
- name: train
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num_examples: 220701
- name: train.1h
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num_examples: 233
- name: train.9h
num_bytes: 1288180
num_examples: 2110
- name: validation
num_bytes: 1463115
num_examples: 2408
download_size: 53296894035
dataset_size: 141097756
- config_name: italian
features:
- name: file
dtype: string
- name: audio
dtype:
audio:
sampling_rate: 16000
- name: text
dtype: string
- name: speaker_id
dtype: int64
- name: chapter_id
dtype: int64
- name: id
dtype: string
splits:
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num_examples: 1262
- name: train
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num_examples: 59623
- name: train.1h
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num_examples: 240
- name: train.9h
num_bytes: 1325927
num_examples: 2173
- name: validation
num_bytes: 732210
num_examples: 1248
download_size: 15395281399
dataset_size: 38958224
- config_name: portuguese
features:
- name: file
dtype: string
- name: audio
dtype:
audio:
sampling_rate: 16000
- name: text
dtype: string
- name: speaker_id
dtype: int64
- name: chapter_id
dtype: int64
- name: id
dtype: string
splits:
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num_examples: 871
- name: train
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num_examples: 37533
- name: train.1h
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num_examples: 236
- name: train.9h
num_bytes: 1305698
num_examples: 2116
- name: validation
num_bytes: 512463
num_examples: 826
download_size: 9982803818
dataset_size: 25548322
Dataset Card for MultiLingual LibriSpeech
Table of Contents
- Dataset Description
- Dataset Structure
- Dataset Creation
- Considerations for Using the Data
- Additional Information
Dataset Description
- Homepage: MultiLingual LibriSpeech ASR corpus
- Repository: [Needs More Information]
- Paper: MLS: A Large-Scale Multilingual Dataset for Speech Research
- Leaderboard: Paperswithcode Leaderboard
Dataset Summary
Deprecated: This legacy dataset doesn't support streaming and is not updated. Use "facebook/multilingual_librispeech" instead.
Multilingual LibriSpeech (MLS) dataset is a large multilingual corpus suitable for speech research. The dataset is derived from read audiobooks from LibriVox and consists of 8 languages - English, German, Dutch, Spanish, French, Italian, Portuguese, Polish.
Supported Tasks and Leaderboards
automatic-speech-recognition
,audio-speaker-identification
: The dataset can be used to train a model for Automatic Speech Recognition (ASR). The model is presented with an audio file and asked to transcribe the audio file to written text. The most common evaluation metric is the word error rate (WER). The task has an active leaderboard which can be found at https://paperswithcode.com/dataset/multilingual-librispeech and ranks models based on their WER.
Languages
The dataset is derived from read audiobooks from LibriVox and consists of 8 languages - English, German, Dutch, Spanish, French, Italian, Portuguese, Polish
Dataset Structure
Data Instances
A typical data point comprises the path to the audio file, usually called file
and its transcription, called text
. Some additional information about the speaker and the passage which contains the transcription is provided.
{'chapter_id': 141231,
'file': '/home/patrick/.cache/huggingface/datasets/downloads/extracted/b7ded9969e09942ab65313e691e6fc2e12066192ee8527e21d634aca128afbe2/dev_clean/1272/141231/1272-141231-0000.flac',
'audio': {'path': '/home/patrick/.cache/huggingface/datasets/downloads/extracted/b7ded9969e09942ab65313e691e6fc2e12066192ee8527e21d634aca128afbe2/dev_clean/1272/141231/1272-141231-0000.flac',
'array': array([-0.00048828, -0.00018311, -0.00137329, ..., 0.00079346,
0.00091553, 0.00085449], dtype=float32),
'sampling_rate': 16000},
'id': '1272-141231-0000',
'speaker_id': 1272,
'text': 'A MAN SAID TO THE UNIVERSE SIR I EXIST'}
Data Fields
file: A path to the downloaded audio file in .flac format.
audio: A dictionary containing the path to the downloaded audio file, the decoded audio array, and the sampling rate. Note that when accessing the audio column:
dataset[0]["audio"]
the audio file is automatically decoded and resampled todataset.features["audio"].sampling_rate
. Decoding and resampling of a large number of audio files might take a significant amount of time. Thus it is important to first query the sample index before the"audio"
column, i.e.dataset[0]["audio"]
should always be preferred overdataset["audio"][0]
.text: the transcription of the audio file.
id: unique id of the data sample.
speaker_id: unique id of the speaker. The same speaker id can be found for multiple data samples.
chapter_id: id of the audiobook chapter which includes the transcription.
Data Splits
Train | Train.9h | Train.1h | Dev | Test | |
---|---|---|---|---|---|
german | 469942 | 2194 | 241 | 3469 | 3394 |
dutch | 374287 | 2153 | 234 | 3095 | 3075 |
french | 258213 | 2167 | 241 | 2416 | 2426 |
spanish | 220701 | 2110 | 233 | 2408 | 2385 |
italian | 59623 | 2173 | 240 | 1248 | 1262 |
portuguese | 37533 | 2116 | 236 | 826 | 871 |
polish | 25043 | 2173 | 238 | 512 | 520 |
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
The dataset consists of people who have donated their voice online. You agree to not attempt to determine the identity of speakers in this dataset.
Considerations for Using the Data
Social Impact of Dataset
[More Information Needed]
Discussion of Biases
[More Information Needed]
Other Known Limitations
[Needs More Information]
Additional Information
Dataset Curators
[Needs More Information]
Licensing Information
Public Domain, Creative Commons Attribution 4.0 International Public License (CC-BY-4.0)
Citation Information
@article{Pratap2020MLSAL,
title={MLS: A Large-Scale Multilingual Dataset for Speech Research},
author={Vineel Pratap and Qiantong Xu and Anuroop Sriram and Gabriel Synnaeve and Ronan Collobert},
journal={ArXiv},
year={2020},
volume={abs/2012.03411}
}
Contributions
Thanks to @patrickvonplaten for adding this dataset.