doteBench v1.0.0

doteBench v1.0.0

doteBench v1.0.0 releases a bilingual benchmark for precise speech editing: 2,081 English and Chinese cases across seven shards, with XML instructions, candidate adapters, deterministic data materialization, and a complete evaluation pipeline. The dataset and evaluation protocol identities are both v1_0.

Assets

• dotebench-1.0.0-py3-none-any.whl: installable Python package.
• dotebench-1.0.0.tar.gz: source distribution.
• dotebench-audio-bundle-v1_0.tar.gz: 1,026 content-addressed WAV files and their provenance and license notices.
• SHA256SUMS: checksums for the three assets above.

The audio bundle includes material from LibriTTS-R, FLEURS, Multilingual LibriSpeech, AISHELL-1, AISHELL-3, and speech generated with Qwen3-TTS VoiceDesign. The audio notice and provenance ledger record the applicable terms for each file. Additional Common Voice audio and generated assets are obtained during local materialization as described in the usage guide.

The data notice identifies transcript sources and their terms, including noncommercial conditions for WenetSpeech and Emo-Emilia portions. The third-party inventory covers adapted CC-BY-SA-3.0 speaker source, Praat GPL obligations for separately installed environments, and IndexTTS-2 model terms. Model checkpoints are obtained from their providers under the applicable terms.

Verification

The release source passed 398 automated tests, data validation across all 2,081 cases, compiler checks, provenance verification, wheel and source build audits, and an installed-wheel CLI smoke test. See README.md for installation and documentation links.