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README.md
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---
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dataset_info:
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features:
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- name:
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dtype:
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- name: split
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dtype: string
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- name: machine_type
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dtype:
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class_label:
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'0': source
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'1': target
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'2': unknown
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- name: section
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dtype: string
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- name: d1p
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dtype:
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class_label:
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dtype:
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class_label:
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names:
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'0':
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'1':
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'2':
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'3': A
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'4': B
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'5': C
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dtype:
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class_label:
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names:
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'0':
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'1':
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'2': none
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- name: d3p
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dtype:
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class_label:
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names:
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'0': none
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- name: audio_path
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dtype: string
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- name: audio
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dtype:
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audio:
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sampling_rate: 16000
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splits:
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- name: train
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num_bytes: 1601921625.0
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num_examples: 5000
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- name: test
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num_bytes: 320384725.0
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num_examples: 1000
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- name: supplemental
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num_bytes: 237068088.0
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num_examples: 700
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download_size: 2134670161
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dataset_size: 2159374438.0
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configs:
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- config_name: default
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data_files:
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- split: train
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path: data/train-*
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- split: test
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path: data/test-*
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- split: supplemental
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path: data/supplemental-*
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---
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---
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annotations_creators: ['no-annotation']
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language: ['en']
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license: ['mit']
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task_categories: ['audio-classification', 'anomaly-detection']
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tags: ['dcase', 'audio', 'anomaly-detection']
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pretty_name: DCASE 2025 Task 2 Dev
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dataset_info:
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features:
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- name: audio
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dtype: audio
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- name: machine_type
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dtype:
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class_label:
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'0': source
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'1': target
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'2': unknown
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- name: d1p
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dtype:
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class_label:
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dtype:
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class_label:
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names:
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'0': 0
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'1': 4
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'2': 5
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'3': A
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'4': B
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'5': C
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dtype:
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class_label:
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names:
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'0': 0
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'1': 5
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'2': none
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- name: d3p
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dtype:
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class_label:
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names:
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'0': none
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---
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# DCASE 2025 Task 2 - Development Dataset
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Attributes `d1v`, `d2v`, `d3v` are encoded as **ClassLabels** for training convenience.
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## Usage
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```python
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from datasets import load_dataset
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dataset = load_dataset('HTill/dcase2025_task2_dev', trust_remote_code=True)
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```
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