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--- |
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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: label |
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dtype: |
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class_label: |
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names: |
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'0': audiophile |
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'1': music |
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'2': sound_event |
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'3': speech |
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splits: |
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- name: test |
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num_bytes: 1965782403.25 |
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num_examples: 3150 |
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download_size: 1609823419 |
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dataset_size: 1965782403.25 |
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configs: |
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- config_name: default |
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data_files: |
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- split: test |
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path: data/test-* |
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--- |
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# AudioTokenBench |
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This is the evaluation dataset for [HiggsTokenizer](https://github.com/boson-ai/higgs-audio/blob/main/tech_blogs/TOKENIZER_BLOG.md). It contains 3150 24khz audio samples across 4 subsets: |
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- **Speech**: 1,000 clips of 10 seconds audio, randomly sampled from [DAPS](https://ccrma.stanford.edu/~gautham/Site/daps.html). |
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- **Music**: 1,000 clips of 10 seconds audio, randomly sampled from [MUSDB](https://sigsep.github.io/datasets/musdb.html). |
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- **Sound Event**: 1,000 clips of 10 seconds audio, randomly sampled from [AudioSet](https://research.google.com/audioset/index.html). |
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- **Audiophile**: Contains 150 clips of 30 seconds audio, curated from eleven high-fidelity test discs. The clips feature both music and sound events, selected for high-quality audio evaluation. |
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For detailed evaluation metrics, please refer to our [blog](https://github.com/boson-ai/higgs-audio/blob/main/tech_blogs/TOKENIZER_BLOG.md) and [github](https://github.com/boson-ai/higgs-audio/tree/main). |
