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