Datasets:
Tasks:
Automatic Speech Recognition
Sub-tasks:
keyword-spotting
Size:
10K<n<100K
ArXiv:
Tags:
speech-recognition
License:
File size: 22,155 Bytes
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---
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
license:
- cc-by-4.0
multilinguality:
- multilingual
size_categories:
- 10K<n<100K
task_categories:
- automatic-speech-recognition
- speech-processing
task_ids:
- speech-recognition
- keyword-spotting
pretty_name: MInDS-14
language_bcp47:
- en
- en-GB
- en-US
- en-AU
- fr
- it
- es
- pt
- de
- nl
- ru
- pl
- cs
- ko
- zh
dataset_info:
- config_name: cs-CZ
features:
- name: audio
dtype:
audio:
sampling_rate: 8000
- name: transcription
dtype: string
- name: english_transcription
dtype: string
- name: intent_class
dtype:
class_label:
names:
'0': abroad
'1': address
'2': app_error
'3': atm_limit
'4': balance
'5': business_loan
'6': card_issues
'7': cash_deposit
'8': direct_debit
'9': freeze
'10': high_value_payment
'11': joint_account
'12': latest_transactions
'13': pay_bill
- name: lang_id
dtype:
class_label:
names:
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'1': de-DE
'2': en-AU
'3': en-GB
'4': en-US
'5': es-ES
'6': fr-FR
'7': it-IT
'8': ko-KR
'9': nl-NL
'10': pl-PL
'11': pt-PT
'12': ru-RU
'13': zh-CN
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features:
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dtype:
audio:
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'11': joint_account
'12': latest_transactions
'13': pay_bill
- name: lang_id
dtype:
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'2': en-AU
'3': en-GB
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'5': es-ES
'6': fr-FR
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'13': zh-CN
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num_examples: 611
download_size: 41061320
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- config_name: en-AU
features:
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dtype:
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dtype: string
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'6': card_issues
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'11': joint_account
'12': latest_transactions
'13': pay_bill
- name: lang_id
dtype:
class_label:
names:
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'1': de-DE
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'13': zh-CN
splits:
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- config_name: en-GB
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- config_name: en-US
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splits:
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- config_name: es-ES
features:
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audio:
sampling_rate: 8000
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dtype:
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names:
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'2': en-AU
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- config_name: it-IT
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audio:
sampling_rate: 8000
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audio:
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audio:
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dtype: string
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names:
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'8': direct_debit
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'10': high_value_payment
'11': joint_account
'12': latest_transactions
'13': pay_bill
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class_label:
names:
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'4': en-US
'5': es-ES
'6': fr-FR
'7': it-IT
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'12': ru-RU
'13': zh-CN
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num_examples: 502
download_size: 32353193
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configs:
- config_name: cs-CZ
data_files:
- split: train
path: cs-CZ/train-*
- config_name: de-DE
data_files:
- split: train
path: de-DE/train-*
- config_name: en-AU
data_files:
- split: train
path: en-AU/train-*
- config_name: en-GB
data_files:
- split: train
path: en-GB/train-*
- config_name: en-US
data_files:
- split: train
path: en-US/train-*
- config_name: es-ES
data_files:
- split: train
path: es-ES/train-*
- config_name: fr-FR
data_files:
- split: train
path: fr-FR/train-*
- config_name: it-IT
data_files:
- split: train
path: it-IT/train-*
- config_name: ko-KR
data_files:
- split: train
path: ko-KR/train-*
- config_name: nl-NL
data_files:
- split: train
path: nl-NL/train-*
- config_name: pl-PL
data_files:
- split: train
path: pl-PL/train-*
- config_name: pt-PT
data_files:
- split: train
path: pt-PT/train-*
- config_name: ru-RU
data_files:
- split: train
path: ru-RU/train-*
- config_name: zh-CN
data_files:
- split: train
path: zh-CN/train-*
---
# 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 = {2104.08524},
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
|