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---
license: cc0-1.0
task_categories:
- text-to-speech
- automatic-speech-recognition
language:
- en
- de
- fr
- bg
- ar
pretty_name: Mumospee_small
tags:
- Speech
- Video
---
# Mumospee: A MUltiMOdal SPEEch Corpus (small)
This is a small version of Mumospee include no more 1000 rows. The full is [here](https://huggingface.co/datasets/meetween/mumospee).
## Overview
At this version it includes below languages and data soruces:
```python
_LANGUAGES = ["en", "bg", "de", "ar", "fr"]
_TAGS = ["CoVoST", "GigaSpeech", "PeopleSpeech", "Librispeech", "LibriTTS", "Emilia", "MOSEL"]
```
## Data Sources
The initial release includes metadata and download scripts for accessing the following publicly available datasets:
- [CoVoST](https://github.com/facebookresearch/covost)
- [GigaSpeech](https://github.com/SpeechColab/GigaSpeech)
- [people-speech](https://mlcommons.org/datasets/peoples-speech/)
- [LibriSpeech](https://www.openslr.org/12)
- [LibriTTS](https://openslr.org/60/)
- [Emilia](https://emilia-dataset.github.io/Emilia-Demo-Page/#dataset)
- [MOSEL](https://huggingface.co/datasets/FBK-MT/mosel)
## Mumospee dataset structure
Mumospee is available at [HuggingFace](https://huggingface.co/datasets/meetween/mumospee) without providing all the audio data directly, but the urls or scripts to access the datasets.
In the metadata csv, each row is a sample representing the metadata of an audio, a video or a clip consisting of the following information:
- "path": the relative path of the audio file to the sample.
- "url": the link to download the parquet containing the audio, video or the clip of it.
- "type": the sample is an audio or video.
- "duration": the duration of the sample in second.
- "language": the language of the video or audio.
- "transcript": the transcript of the video or audio.
- "tag": the origin of the sample.
- "split": the sample is in split, test, or validation section in the original dataset.
- "license": the license to use this sample.
Here is an example sample:
```json
{
"path": "3660-172183-0000.flac",
"url": "https://huggingface.co/datasets/meetween/mumospee_librispeech/resolve/main/librispeech-parquet/dev-other.parquet",
"type": "audio",
"duration": 5.405,
"language": "en",
"transcript": "GERAINT AS HE HAD BEEN USED TO DO WHEN HE WAS AT ARTHUR'S COURT FREQUENTED TOURNAMENTS",
"tag": "Librispeech",
"split": "validation",
"license": "CC-BY-4.0"
}
```
## Example Usage
```python
dataset= load_dataset("meetween/mumospee_small", trust_remote_code=True)
print(dataset)
# To get the first row of the dataset.
sample_first = dataset["train"][0]
```
The defaul outputs all the samples from train split. To get another splits:
```python
# To get the dataset from test or validation split
dataset_test = load_dataset("meetween/mumospee_small", "test", trust_remote_code=True)
dataset_validation = load_dataset("meetween/mumospee_small", "validation", trust_remote_code=True)
```
- ### Filters ###
There are filters to select dataset samples from specific groups:
```python
# To get the dataset of langauge "en".
dataset= load_dataset("meetween/mumospee_small", "test", language="en", trust_remote_code=True)
# To get the dataset from MOSEL.
dataset= load_dataset("meetween/mumospee_small", "train", tag="MOSEL", trust_remote_code=True)
# You can also add combination of language and tag: get English from CoVoST from test split.
dataset= load_dataset("meetween/mumospee_small", "test", language="en", tag="CoVoST", trust_remote_code=True)
```
Note: keep in mind that if a filter combination (including split) results to no dataset, you may get an value error like below:
```python
ValueError: Instruction "train" corresponds to no data!
```
Also, make sure the values are from `_LANGUAGES` and `_TAG`.
- ### Download audios ###
You can download the parquet files with the audios data by using the `download_audio` parameter (the default is `None`):
```python
dataset= load_dataset("meetween/mumospee_small", "test", download_audio=True, language="en", trust_remote_code=True)
```
## License
The metadata and download scripts are publicly available under a CC0 license. While the metadata itself is open, users must comply with the licensing terms of each underlying dataset.
--- |