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---
dataset_info:
features:
- name: audio
dtype: audio
- name: label
dtype:
class_label:
names:
'0': audiophile
'1': music
'2': sound_event
'3': speech
splits:
- name: test
num_bytes: 1965782403.25
num_examples: 3150
download_size: 1609823419
dataset_size: 1965782403.25
configs:
- config_name: default
data_files:
- split: test
path: data/test-*
---
# AudioTokenBench
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:
- **Speech**: 1,000 clips of 10 seconds audio, randomly sampled from [DAPS](https://ccrma.stanford.edu/~gautham/Site/daps.html).
- **Music**: 1,000 clips of 10 seconds audio, randomly sampled from [MUSDB](https://sigsep.github.io/datasets/musdb.html).
- **Sound Event**: 1,000 clips of 10 seconds audio, randomly sampled from [AudioSet](https://research.google.com/audioset/index.html).
- **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.
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). |