--- license: other task_categories: - audio-classification pretty_name: SRE Dataset configs: - config_name: default data_files: - split: train path: "data/train/audio/*.tar" - split: validation path: "data/validation/audio/*.tar" - split: test path: "data/test/audio/*.tar" tags: - audio - speech - speaker-recognition - sre - webdataset --- # Yougen/sre_dataset Speaker Recognition (SRE) speech dataset, packed as **WebDataset tar shards**. ## Layout ``` data/ train/ metadata.csv audio/ train-000.tar train-001.tar ... validation/ metadata.csv audio/ validation-000.tar ... test/ metadata.csv audio/ test-000.tar ... ``` Shard counts: - `train`: 203 tar shard(s) - `validation`: 4 tar shard(s) - `test`: 4 tar shard(s) Inside each tar, every sample is a pair sharing a unique key: ``` .wav # raw audio bytes .json # {"id":..., "rel_path":..., "wav_format":..., "duration":..., "label_str":..., "label":...} ``` `metadata.csv` columns: `key, shard, id, rel_path, wav_format, duration, label_str, label` ## Loading ```python from datasets import load_dataset ds = load_dataset("Yougen/sre_dataset") print(ds) print(ds["train"][0]) # sample keys: 'wav' (decoded audio), 'json' (metadata), '__key__', '__url__' ``` For streaming (no full download needed): ```python ds = load_dataset("Yougen/sre_dataset", streaming=True) for example in ds["train"]: print(example["__key__"], example["json"]["label_str"]) break ``` HuggingFace's `webdataset` builder will automatically pair `.wav` with `.json` inside every tar and decode the audio.