---
dataset_info:
  features:
  - name: audio_id
    dtype: string
  - name: language
    dtype:
      class_label:
        names:
          '0': en
          '1': de
          '2': fr
          '3': es
          '4': pl
          '5': it
          '6': ro
          '7': hu
          '8': cs
          '9': nl
          '10': fi
          '11': hr
          '12': sk
          '13': sl
          '14': et
          '15': lt
          '16': en_accented
  - name: audio
    dtype:
      audio:
        sampling_rate: 16000
  - name: sentence
    dtype: string
  - name: unified_entities
    sequence:
      class_label:
        names:
          '0': B-cell_line
          '1': B-character_name
          '2': B-language
          '3': B-disease
          '4': B-event
          '5': B-organization
          '6': B-character
          '7': B-origin
          '8': B-other
          '9': B-dish
          '10': B-relationship
          '11': B-artifact
          '12': B-work_of_art
          '13': B-facility
          '14': B-product
          '15': B-amenity
          '16': B-rating
          '17': B-actor
          '18': B-date
          '19': B-ratings_average
          '20': B-quantity
          '21': B-dna
          '22': B-quote
          '23': B-title
          '24': B-song
          '25': B-genre
          '26': B-cuisine
          '27': B-soundtrack
          '28': B-ordinal_number
          '29': B-protein
          '30': B-collection
          '31': B-money
          '32': B-person
          '33': B-project
          '34': B-group
          '35': B-review
          '36': B-percent
          '37': B-law
          '38': B-director
          '39': B-award
          '40': B-chemical
          '41': B-geopolitical_area
          '42': B-rna
          '43': B-restaurant
          '44': B-location
          '45': B-opinion
          '46': B-cell_type
          '47': B-trailer
          '48': B-cardinal_number
          '49': B-plot
          '50': B-corporation
          '51': B-time
          '52': I-cell_line
          '53': I-character_name
          '54': I-language
          '55': I-disease
          '56': I-event
          '57': I-organization
          '58': I-character
          '59': I-origin
          '60': I-other
          '61': I-dish
          '62': I-relationship
          '63': I-artifact
          '64': I-work_of_art
          '65': I-facility
          '66': I-product
          '67': I-amenity
          '68': I-rating
          '69': I-actor
          '70': I-date
          '71': I-ratings_average
          '72': I-quantity
          '73': I-dna
          '74': I-quote
          '75': I-title
          '76': I-song
          '77': I-genre
          '78': I-cuisine
          '79': I-soundtrack
          '80': I-ordinal_number
          '81': I-protein
          '82': I-collection
          '83': I-money
          '84': I-person
          '85': I-project
          '86': I-group
          '87': I-review
          '88': I-percent
          '89': I-law
          '90': I-director
          '91': I-award
          '92': I-chemical
          '93': I-geopolitical_area
          '94': I-rna
          '95': I-restaurant
          '96': I-location
          '97': I-opinion
          '98': I-cell_type
          '99': I-trailer
          '100': I-cardinal_number
          '101': I-plot
          '102': I-corporation
          '103': I-time
          '104': O
  - name: ontonotes_entities
    sequence:
      class_label:
        names:
          '0': O
          '1': B-cardinal number
          '2': B-date
          '3': I-date
          '4': B-person
          '5': I-person
          '6': B-group
          '7': B-geopolitical area
          '8': I-geopolitical area
          '9': B-law
          '10': I-law
          '11': B-organization
          '12': I-organization
          '13': B-percent
          '14': I-percent
          '15': B-ordinal number
          '16': B-money
          '17': I-money
          '18': B-work of art
          '19': I-work of art
          '20': B-facility
          '21': B-time
          '22': I-cardinal number
          '23': B-location
          '24': B-quantity
          '25': I-quantity
          '26': I-group
          '27': I-location
          '28': B-product
          '29': I-time
          '30': B-event
          '31': I-event
          '32': I-facility
          '33': B-language
          '34': I-product
          '35': I-ordinal number
          '36': I-language
  splits:
  - name: de
    num_bytes: 1104049942.714
    num_examples: 1966
  - name: fr
    num_bytes: 1054225315.44
    num_examples: 1656
  - name: nl
    num_bytes: 600447374.88
    num_examples: 1120
  - name: es
    num_bytes: 1152365703.024
    num_examples: 1512
  download_size: 3330860792
  dataset_size: 3911088336.0580006
---
# Dataset Card for "spoken-ner"

[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)