MInDS-14

Summary

• Introduction
• Dataset Structure
• Reference
• License
• Citation

Introduction

MInDS-14 is a training and evaluation resource for the 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.

Dataset 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": ".../datasets/downloads/extracted/3ebe2265b2f102203be5e64fa8e533e0c6742e72268772c8ac1834c5a1a921e3/fr-FR~ADDRESS/response_4.wav",
    "audio": {
        "path": ".../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 dataset has the following fields:

• path (str): Path to the audio file.
• audio (dict): Audio object including the loaded audio array, sampling rate, and path to the audio file.
• 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.

Reference

We would like to acknowledge Daniela Gerz et al. for creating and maintaining the MInDS-14 dataset as a valuable resource for the speech and natural language processing research community. For more information about the MInDS-14 dataset and its creators, please refer to the MInDS-14 paper.

License

The dataset has been released under the Creative Commons Attribution 4.0 International License (CC-BY 4.0).

Citation

@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}
}