| --- |
| pretty_name: Consumer Speech Declipping — Clean Pool v2 |
| task_categories: |
| - audio-to-audio |
| tags: |
| - audio |
| - speech |
| - declipping |
| - clean-reference |
| - 48khz |
| --- |
| |
| # Consumer Speech Declipping — Clean Pool v2 |
|
|
| The current release is in [consumer-speech-v2/](https://huggingface.co/datasets/anthonyleedom/test2/tree/main/consumer-speech-v2). |
| It uses directly readable tar |
| shards containing FLAC audio, rather than a compressed archive that needs extraction. |
| The older dataset.tar.zst release remains available for historical work. |
|
|
| ## Contents |
|
|
| - 150,000 unique clean six-second training windows: 250 hours including explicit joins/padding. |
| - 512 fixed validation pairs and 512 fixed test pairs. |
| - Mono, 48 kHz, PCM24 FLAC. |
| - Training references receive live degradation after collation in the declipping project. |
| - No codec routes. Validation/test inputs and references are fixed. |
| - Bundle footprint: 70.35 GB. |
| - Bundle identity (SHA256 of canonical manifest): 9eff7c0e2e3297591e9fd508febcf86a162636f15a09afdfb8018609ed351a27 |
|
|
| ## Files |
|
|
| - bundle.json: manifest, shard checksums, counts and build identity. |
| - plan.json: frozen source selections and codec-free render policy. |
| - items.parquet: strict item index, audio offsets and source lineage. |
| - audit.json: stored-data distribution and source exposure. |
| - shards/: directly readable tar files containing clean.flac and render records; |
| fixed nonidentity evaluation examples also have degraded.flac. |
|
|
| Training records use identity storage to represent the clean reference once. This is |
| not identity-only training. The live policy requests 20% preservation examples and |
| uses nominal mild/moderate/severe/extreme weights of 20:40:15:5 among nonidentity |
| draws. Actual measured damage is reported separately by the live training audit. |
|
|
| ## Sources and training sampling |
|
|
| The clean pool includes EARS, VCTK mic1, HiFi TTS, Espresso originals, and approved |
| Lien/Meru microphone recordings. Original speaker splits are preserved. Lien/Meru |
| retain all approved intervals after quiet/clipping exclusions; microphone views are |
| not treated as additional speakers. Espresso is training-only and its speaker |
| overlap is unverified. |
|
|
| Training draw shares are EARS 50%, VCTK 30%, HiFi 15%, Espresso 3%, Lien 1%, Meru 1%. |
| These shares are independent of the stored window counts. HiFi fills the remaining |
| unique pool capacity. The sampler excludes repeated speakers/performances within an |
| effective batch and the two comparison architectures share a reproducible draw schedule. |
|
|
| Underlying source licenses and permissions apply. This combined release does not |
| grant a new blanket license over its constituent recordings. |
|
|
| ## Download on Vast |
|
|
| After publication, pin the full Hugging Face commit SHA shown in the Files history. |
| The uploader also writes that exact SHA to its local published.json receipt. |
|
|
| ~~~sh |
| hf download anthonyleedom/test2 --repo-type dataset --revision FULL_COMMIT_SHA --include 'consumer-speech-v2/*' --local-dir /workspace/datasets |
| ~~~ |
|
|
| The bundle will be at /workspace/datasets/consumer-speech-v2. Download only this folder. |
| No tar extraction is required. Use the declipping project's declip-data validation |
| and prepare-comparison commands on that directory before training. |
|
|
