intermediateaudio
AudioSet Event Classification
Multi-label audio event tagging following the AudioSet ontology for weak supervision.
Configuration Fileconfig.yaml
annotation_task_name: "AudioSet Event Classification"
port: 8000
# Data configuration
data_files:
- "data/audio_clips.json"
item_properties:
id_key: id
text_key: text
# Annotation schemes
annotation_schemes:
# Human sounds
- annotation_type: multiselect
name: human_sounds
description: "Human sounds present (select all that apply)"
labels:
- Speech
- Singing
- Shout
- Whisper
- Laughter
- Crying/sobbing
- Cough
- Sneeze
- Breathing
- Footsteps
- Clapping
- None
# Animal sounds
- annotation_type: multiselect
name: animal_sounds
description: "Animal sounds present (select all that apply)"
labels:
- Dog bark
- Cat meow
- Bird chirp/song
- Rooster crow
- Insect buzz
- Horse neigh
- Cow moo
- None
# Music and instruments
- annotation_type: multiselect
name: music_sounds
description: "Music and instruments present (select all that apply)"
labels:
- Music
- Guitar
- Piano
- Drums
- Violin
- Singing (musical)
- Electronic music
- None
# Environmental sounds
- annotation_type: multiselect
name: environment_sounds
description: "Environmental sounds present (select all that apply)"
labels:
- Wind
- Rain
- Thunder
- Water (stream/river)
- Fire crackling
- Traffic noise
- Siren
- Bell
- Door slam
- None
# Mechanical sounds
- annotation_type: multiselect
name: mechanical_sounds
description: "Mechanical/vehicle sounds present (select all that apply)"
labels:
- Car engine
- Motorcycle
- Train
- Aircraft
- Power tools
- Keyboard typing
- Phone ringing
- None
# Confidence rating
- annotation_type: likert
name: confidence
description: "How confident are you in your labels?"
size: 5
min_label: "Not confident"
max_label: "Very confident"
# Notes
- annotation_type: text
name: notes
description: "Additional sounds or notes (optional)"
textarea: false
required: false
# User settings
allow_all_users: true
instances_per_annotator: 200
# Output
output_annotation_dir: "annotation_output/"
output_annotation_format: "json"
Get This Design
This design is available in our showcase. Copy the configuration below to get started.
Quick start:
# Create your project folder mkdir audioset-event-classification cd audioset-event-classification # Copy config.yaml from above potato start config.yaml
Details
Annotation Types
multiselect
Domain
AudioSpeech
Use Cases
audio classificationsound event detectionweak labeling
Tags
audioaudiosetmulti-labelevent classification
Related Designs
Audio Transcription Review
Review and correct automatic speech recognition transcriptions with waveform visualization.
likertmultiselect
Music Tagging
Multi-label music tagging following MagnaTagATune dataset format for instrument and genre annotation.
multiselectlikert
Respiratory Sound Classification
Classify lung and respiratory sounds for medical diagnosis following ICBHI 2017 Challenge format.
radiomultiselect