Acoustic Scene Classification

annotation_task_name: "Acoustic Scene Classification"

port: 8000

# Data configuration
data_files:
  - "data/scenes.json"

item_properties:
  id_key: id
  text_key: text

# Annotation schemes
annotation_schemes:
  # Primary scene category
  - annotation_type: radio
    name: scene_category
    description: "Select the acoustic scene/environment"
    labels:
      - name: Airport
        key_value: "1"
      - name: Bus
        key_value: "2"
      - name: Metro station
        key_value: "3"
      - name: Metro (inside train)
        key_value: "4"
      - name: Park
        key_value: "5"
      - name: Public square
        key_value: "6"
      - name: Shopping mall
        key_value: "7"
      - name: Street (pedestrian)
        key_value: "8"
      - name: Street (traffic)
        key_value: "9"
      - name: Tram
        key_value: "0"
    sequential_key_binding: true

  # Indoor/outdoor
  - annotation_type: radio
    name: environment_type
    description: "Is this primarily indoor or outdoor?"
    labels:
      - Indoor
      - Outdoor
      - Mixed/transitional
      - Cannot determine

  # Scene clarity
  - annotation_type: radio
    name: scene_clarity
    description: "How clearly identifiable is the scene?"
    labels:
      - Very clear (unmistakable)
      - Clear (confident identification)
      - Ambiguous (could be multiple scenes)
      - Unclear (cannot identify)

  # Secondary sounds
  - annotation_type: multiselect
    name: prominent_sounds
    description: "What sounds are most prominent? (Select up to 3)"
    labels:
      - Human speech/chatter
      - Vehicle noise
      - Footsteps
      - Announcements/PA system
      - Nature sounds (birds, wind)
      - Music
      - Machinery/equipment
      - Silence/quiet

  # Confidence rating
  - annotation_type: likert
    name: confidence
    description: "Confidence in your scene classification"
    size: 5
    min_label: "Low"
    max_label: "High"

# User settings
allow_all_users: true
instances_per_annotator: 200

# Output
output_annotation_dir: "annotation_output/"
output_annotation_format: "json"