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Datasets:
AudioCC-Lab
/
PICSAFEv1

Tasks:
Audio Classification
Modalities:
Text
Audio
Formats:
json
Size:
10K - 100K
Tags:
audio
multi-label-classification
speech-quality
Libraries:
Datasets
pandas
Polars
License:
Dataset card Data Studio Files
xet
 Community
1
chuang.li commited on
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1 Parent(s): 318dca0

Add PICSAFEv1 audio dataset

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  1. README.md +87 -0
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README.md ADDED
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+ ---
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+ license: other
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+ task_categories:
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+ - audio-classification
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+ tags:
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+ - audio
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+ - multi-label-classification
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+ - speech-quality
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+ configs:
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+ - config_name: default
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+ data_files:
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+ path: data/**
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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: id
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+ dtype: string
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+ - name: source
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+ dtype: string
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+ - name: source_path
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+ dtype: string
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+ - name: tags
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+ sequence: string
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+ splits:
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+ - name: test
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+ num_examples: 10728
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+ ---
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+
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+ # Speech Quality Test Labels
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+
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+ This dataset contains 10,728 audio files with multi-label annotations from 14 source datasets. It is intended as a test split for speech quality and audio-content classification.
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+
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+ ## Dataset structure
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+
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+ - `audio`: audio decoded from the file referenced by `file_name` in the metadata.
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+ - `id`: globally unique sample identifier. Its `[source]` prefix is retained from the original metadata.
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+ - `source`: source dataset name parsed from `id`.
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+ - `source_path`: path relative to the common directory of that source in the original manifest.
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+ - `tags`: multi-label annotations represented as a list of strings.
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+
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+ The original machine-specific absolute paths have intentionally been removed.
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+
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+ ## Source distribution
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+
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+ | Source | Samples |
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+ | --- | ---: |
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+ | CSTR-NAM-TIMIT-Plus | 842 |
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+ | DNS5_LibriVox | 510 |
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+ | EARS | 1,042 |
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+ | MSceneSpeech | 1,000 |
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+ | NISQA | 724 |
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+ | SOMOSv2 | 500 |
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+ | TencentCorpus | 1,010 |
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+ | VCTK | 1,000 |
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+ | WenetSpeech | 600 |
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+ | Whisper40 | 500 |
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+ | WSJ | 1,000 |
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+ | zhvoice | 500 |
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+ | LibriTTS-R | 500 |
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+ | LibriTTS | 1,000 |
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+
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+ ## Labels
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+
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+ The 33 labels are:
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+
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+ `Nspk`, `distortion`, `emotional`, `enhanced`, `excessive_sibilance`, `fast_speed`, `female`, `high_pitch`, `imperceptible_noise_level`, `instantaneous_noise`, `low_noise_level`, `low_pitch`, `male`, `microphone_popping`, `mid_high_noise_level`, `music_or_effect`, `nb_noise`, `non_binary`, `non_speech`, `read_speech`, `real_recording`, `regular_pitch`, `regular_speed`, `reverberation`, `singing_voice`, `slow_speed`, `speech_overlap`, `spontaneous_speech`, `synthetic`, `vocal_sound`, `wb_noise`, `whispered_speech`, and `wrong_transcript`.
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+
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+ ## Usage
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+
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+ ```python
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+ from datasets import load_dataset
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+
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+ dataset = load_dataset("YOUR_NAMESPACE/YOUR_DATASET_NAME", split="test")
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+ ```
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+
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+ For a local checkout:
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+
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+ ```python
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+ dataset = load_dataset("audiofolder", data_dir="data", split="test")
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+ ```
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+
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+ ## Licensing and limitations
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+
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+ The audio and annotations remain subject to their source datasets' terms. The license and redistribution permissions were not present in the source TSV; confirm them and replace this section with the final license terms before making the repository public.
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+
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+ The labels may be imbalanced and should not be interpreted as exhaustive descriptions of each recording.
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