Datasets:
Tasks:
Automatic Speech Recognition
Sub-tasks:
keyword-spotting
Size:
10K<n<100K
ArXiv:
Tags:
speech-recognition
License:
annotations_creators: | |
- expert-generated | |
- crowdsourced | |
- machine-generated | |
language_creators: | |
- crowdsourced | |
- expert-generated | |
language: | |
- en | |
- fr | |
- it | |
- es | |
- pt | |
- de | |
- nl | |
- ru | |
- pl | |
- cs | |
- ko | |
- zh | |
language_bcp47: | |
- en | |
- en-GB | |
- en-US | |
- en-AU | |
- fr | |
- it | |
- es | |
- pt | |
- de | |
- nl | |
- ru | |
- pl | |
- cs | |
- ko | |
- zh | |
license: | |
- cc-by-4.0 | |
multilinguality: | |
- multilingual | |
pretty_name: 'MInDS-14' | |
size_categories: | |
- 10K<n<100K | |
task_categories: | |
- automatic-speech-recognition | |
- speech-processing | |
task_ids: | |
- speech-recognition | |
- keyword-spotting | |
# MInDS-14 | |
## Dataset Description | |
- **Fine-Tuning script:** [pytorch/audio-classification](https://github.com/huggingface/transformers/tree/main/examples/pytorch/audio-classification) | |
- **Paper:** [Multilingual and Cross-Lingual Intent Detection from Spoken Data](https://arxiv.org/abs/2104.08524) | |
- **Total amount of disk used:** ca. 500 MB | |
MINDS-14 is training and evaluation resource for intent detection task with spoken data. It covers 14 | |
intents extracted from a commercial system in the e-banking domain, associated with spoken examples in 14 diverse language varieties. | |
## Example | |
MInDS-14 can be downloaded and used as follows: | |
```py | |
from datasets import load_dataset | |
minds_14 = load_dataset("PolyAI/minds14", "fr-FR") # for French | |
# to download all data for multi-lingual fine-tuning uncomment following line | |
# minds_14 = load_dataset("PolyAI/all", "all") | |
# see structure | |
print(minds_14) | |
# load audio sample on the fly | |
audio_input = minds_14["train"][0]["audio"] # first decoded audio sample | |
intent_class = minds_14["train"][0]["intent_class"] # first transcription | |
intent = minds_14["train"].features["intent_class"].names[intent_class] | |
# use audio_input and language_class to fine-tune your model for audio classification | |
``` | |
## Dataset Structure | |
We show detailed information the example configurations `fr-FR` of the dataset. | |
All other configurations have the same structure. | |
### Data Instances | |
**fr-FR** | |
- Size of downloaded dataset files: 471 MB | |
- Size of the generated dataset: 300 KB | |
- Total amount of disk used: 471 MB | |
An example of a datainstance of the config `fr-FR` looks as follows: | |
``` | |
{ | |
"path": "/home/patrick/.cache/huggingface/datasets/downloads/extracted/3ebe2265b2f102203be5e64fa8e533e0c6742e72268772c8ac1834c5a1a921e3/fr-FR~ADDRESS/response_4.wav", | |
"audio": { | |
"path": "/home/patrick/.cache/huggingface/datasets/downloads/extracted/3ebe2265b2f102203be5e64fa8e533e0c6742e72268772c8ac1834c5a1a921e3/fr-FR~ADDRESS/response_4.wav", | |
"array": array( | |
[0.0, 0.0, 0.0, ..., 0.0, 0.00048828, -0.00024414], dtype=float32 | |
), | |
"sampling_rate": 8000, | |
}, | |
"transcription": "je souhaite changer mon adresse", | |
"english_transcription": "I want to change my address", | |
"intent_class": 1, | |
"lang_id": 6, | |
} | |
``` | |
### Data Fields | |
The data fields are the same among all splits. | |
- **path** (str): Path to the audio file | |
- **audio** (dict): Audio object including loaded audio array, sampling rate and path ot audio | |
- **transcription** (str): Transcription of the audio file | |
- **english_transcription** (str): English transcription of the audio file | |
- **intent_class** (int): Class id of intent | |
- **lang_id** (int): Id of language | |
### Data Splits | |
Every config only has the `"train"` split containing of *ca.* 600 examples. | |
## Dataset Creation | |
[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | |
## Considerations for Using the Data | |
### Social Impact of Dataset | |
[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | |
### Discussion of Biases | |
[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | |
### Other Known Limitations | |
[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | |
## Additional Information | |
### Dataset Curators | |
[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | |
### Licensing Information | |
All datasets are licensed under the [Creative Commons license (CC-BY)](https://creativecommons.org/licenses/). | |
### Citation Information | |
``` | |
@article{DBLP:journals/corr/abs-2104-08524, | |
author = {Daniela Gerz and | |
Pei{-}Hao Su and | |
Razvan Kusztos and | |
Avishek Mondal and | |
Michal Lis and | |
Eshan Singhal and | |
Nikola Mrksic and | |
Tsung{-}Hsien Wen and | |
Ivan Vulic}, | |
title = {Multilingual and Cross-Lingual Intent Detection from Spoken Data}, | |
journal = {CoRR}, | |
volume = {abs/2104.08524}, | |
year = {2021}, | |
url = {https://arxiv.org/abs/2104.08524}, | |
eprinttype = {arXiv}, | |
eprint = {2104.085241}, | |
timestamp = {Mon, 26 Apr 2021 17:25:10 +0200}, | |
biburl = {https://dblp.org/rec/journals/corr/abs-2104-08524.bib}, | |
bibsource = {dblp computer science bibliography, https://dblp.org} | |
} | |
``` | |
### Contributions | |
Thanks to [@patrickvonplaten](https://github.com/patrickvonplaten) for adding this dataset | |