metadata

language:
  - fr
license: cc-by-4.0
size_categories:
  - 1K<n<10K
task_categories:
  - automatic-speech-recognition
pretty_name: PxCorpus
dataset_info:
  features:
    - name: audio
      dtype: audio
    - name: file_name
      dtype: string
    - name: transcription
      dtype: string
    - name: audio_name
      dtype: string
    - name: ner
      dtype: string
    - name: speaker_id
      dtype: int64
    - name: speaker_age_range
      dtype: string
    - name: speaker_gender
      dtype: string
    - name: speaker_category
      dtype: string
    - name: drug
      sequence: string
    - name: d_dos_val
      sequence: string
    - name: d_dos_up
      sequence: string
    - name: dur_val
      sequence: string
    - name: dur_ut
      sequence: string
    - name: dos_val
      sequence: string
    - name: dos_uf
      sequence: string
    - name: rhythm_tdte
      sequence: string
    - name: rhythm_perday
      sequence: string
    - name: inn
      sequence: string
    - name: d_dos_form
      sequence: string
    - name: freq_ut
      sequence: string
    - name: rhythm_hour
      sequence: string
    - name: dos_cond
      sequence: string
    - name: qsp_val
      sequence: string
    - name: qsp_ut
      sequence: string
    - name: cma_event
      sequence: string
    - name: roa
      sequence: string
    - name: A
      sequence: string
    - name: max_unit_val
      sequence: string
    - name: max_unit_ut
      sequence: string
    - name: max_unit_uf
      sequence: string
    - name: d_dos_form_ext
      sequence: string
    - name: rhythm_rec_ut
      sequence: string
    - name: fasting
      sequence: string
    - name: freq_int_v1
      sequence: string
    - name: freq_int_v1_ut
      sequence: string
    - name: re_val
      sequence: string
    - name: re_ut
      sequence: string
    - name: freq_val
      sequence: string
    - name: freq_int_v2
      sequence: string
    - name: rhythm_rec_val
      sequence: string
    - name: min_gap_ut
      sequence: string
    - name: freq_startday
      sequence: string
    - name: freq_int_v2_ut
      sequence: string
    - name: min_gap_val
      sequence: string
    - name: freq_days
      sequence: string
    - name: medical_terms
      sequence: string
  splits:
    - name: train
      num_bytes: 252725374.904
      num_examples: 1127
    - name: test
      num_bytes: 175599765
      num_examples: 570
    - name: dev
      num_bytes: 61546023
      num_examples: 283
  download_size: 465682214
  dataset_size: 489871162.90400004
configs:
  - config_name: default
    data_files:
      - split: train
        path: data/train-*
      - split: test
        path: data/test-*
      - split: dev
        path: data/dev-*
tags:
  - medical

PxCorpus : A Spoken Drug Prescription Dataset in French

PxCorpus is to the best of our knowledge, the first spoken medical drug prescriptions corpus to be distributed. It contains 4 hours of transcribed and annotated dialogues of drug prescriptions in French acquired through an experiment with 55 participants experts and non-experts in drug prescriptions.

The automatic transcriptions were verified by human effort and aligned with semantic labels to allow training of NLP models. The data acquisition protocol was reviewed by medical experts and permit free distribution without breach of privacy and regulation.

Overview of the Corpus

The experiment has been performed in wild conditions with naive participants and medical experts. In total, the dataset includes 2067 recordings of 55 participants (38% non-experts, 25% doctors, 36% medical practitioners), manually transcribed and semantically annotated.

Category	Sessions	Recordings	Time(m)
Medical experts	258	434	94.83
Doctors	230	570	105.21
Non experts	415	977	62.13
Total	903	1981	262.27

License

We hope that that the community will be able to benefit from the dataset
which is distributed with an attribution 4.0 International (CC BY 4.0) Creative Commons licence.

How to cite this corpus

If you use the corpus or need more details please refer to the following paper: A spoken drug prescription datset in French for spoken Language Understanding

@InProceedings{Kocabiyikoglu2022, author = "Alican Kocabiyikoglu and Fran{\c c}ois Portet and Prudence Gibert and Hervé Blanchon and Jean-Marc Babouchkine and Gaëtan Gavazzi", title = "A spoken drug prescription datset in French for spoken Language Understanding", booktitle = "13th Language Ressources and Evaluation Conference (LREC 2022)", year = "2022", location = "Marseille, France" }

Dataset features

path -- Audio name
text -- Audio utterance
ner -- Semantic annotation from the original dataset
speaker_id -- Speaker ID
speaker_age_range -- Speaker age range
speaker_gender -- Speaker gender
speaker_category -- Speaker category (doctor, expert, non-expert)
Other column names are for the occurences of each NER tag, could be useful for computing some metrics