Interspeech has no badge-granting artifact committee; the artifact culture is community-enforced instead. Reviewers listen to your samples, and post-publication readers judge the paper by whether the recipe reproduces. This skill treats artifacts in the two states an Interspeech cycle forces: anonymous during review, permanent after acceptance. Check the current author instructions for what may be attached versus linked — attachment rules vary by cycle.
| Artifact | Review-time form | Post-acceptance form |
|---|---|---|
| Audio samples (TTS/VC/enhancement) | Anonymous static demo page or attached files | Permanent samples page linked in camera-ready |
| Code + training recipe | Anonymized repo (no usernames in history/CI) | Public repo, tagged at the paper's commit |
| Model checkpoints | Usually withheld (size, identity risk) | Hosted release with license and card |
| Data/corpus contribution | Described + license stated in paper | Archived with DOI, documented splits |
| Scoring/protocol scripts | In the anonymized repo | In the public repo — the piece most reused |
Audio demos are where Interspeech anonymity dies. Before the deadline, sweep:
Speech artifacts carry legal and ethical weight that generic ML artifacts do not:
A speech result is reproducible when a stranger can regenerate the number, not just run the model. Package for the number:
release/
├── README.md # env, corpus versions + licenses, one command per table row
├── recipe/ # data prep → training → decoding, in run order
├── conf/ # exact configs/hyperparameters used in the paper
├── scoring/ # the WER/EER/MOS-analysis scripts and text-norm rules
├── RESULTS.md # expected outputs with tolerances (seeds, CI width)
└── LICENSE # code license + data-license pointers
The scoring/ directory matters most at this venue: WER moves with text
normalization and EER with trial lists, so publish the measurement, not only the
model (see interspeech-reproducibility).
Concrete ways speech artifacts have deanonymized their authors — sweep for each:
<university>.github.io/<lab-project>/ linked straight
from the anonymous PDF.git log --format='%ae' | sort -u before sharing).| Situation | Community-normal release |
|---|---|
| ASR/SSL encoder on licensed-but-public corpora | Recipe + checkpoint |
| Speaker-verification model on VoxCeleb-family data | Recipe + checkpoint, license noted |
| TTS/VC on a consenting or synthetic voice | Recipe + checkpoint + samples |
| TTS/VC cloning a real speaker without release rights | Recipe + samples only; no checkpoint |
| Anything trained on scraped, unlicensed audio | Describe honestly; release nothing derived |
[Artifact inventory] samples / code / checkpoints / data / scoring — state of each
[Anonymity sweep] host, page, metadata, voice-identifiability findings
[License chain] corpus licenses → what may be redistributed
[Consent/dual-use] speaker permission status; release decision + rationale
[Release plan] what flips public at camera-ready, where it lives permanently
[Gaps] <ordered fixes>
Attachment size limits, link policies, and any new artifact requirements are
cycle-volatile — verify on the current author pages (2026 sources logged in
resources/official-source-map.md, checked 2026-07-08).