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Final Publication Acceptance
GitHub Release and PyPI 1.4.22 are both published. Both distributions were downloaded from official PyPI and match the accepted GitHub assets by SHA-256 and size:
funasr-1.4.22-py3-none-any.whl: 1014515 bytes; SHA-25683525bb5f185e29032f840f232eb226080ffa37e9d86988893faa225e609dc35.funasr-1.4.22.tar.gz: 1069356 bytes; SHA-256db8c67f2bf36df25bd26e724d7a432ec04667e877cd81119d8d388a58ae82eb0.
FunASR 1.4.22
Source: dedefbf643289098e5473fa0cc6ce085e2e9533e / tag v1.4.22.
Fix
Deliver #3841: merge_length_s passed to generate() takes precedence over construction-time/default merge length. Deliver #3833: the dynamic silence schedule is evaluated per frame using the current speech-segment duration, not accumulated chunk time; the fixed-threshold opt-out remains available.
This does not claim pretrained ASR quality, Windows/NPU acceptance or a full repository-suite result.
The separately released funasr-onnx==0.4.8 and funasr-torch==0.1.6 have their own tags, packages and verification. This root-package release does not republish them. The separately reproduced no-LFR frontend exception is not fixed by this release.
Verification Scope
- New candidate release/README checks: 45 cases, 0 skips. Related docs/package/release checks: 104 cases, 2 explicitly recorded skips; no failures or errors.
- Actual installed candidate wheel: 9 CPU unit contracts covering per-call/construction/default merge length and dynamic/fixed VAD scheduling. Their mocked boundaries are not hardware inference. All 439 package files and 13 entrypoints match the accepted source.
- Reused the 32 AutoModel and 24 VAD real L20Z FP32 analytic integration cases from #3841/#3833 after rehashing their sealed raw receipts and binding the exact source to the installed wheel. Their separate prior runs record 216521 CUDA events in total. This is not a new GPU execution, BF16 run or pretrained-quality validation.
- Exact release-head and merged-main CI were accepted with actual logs/artifacts. The final-tag workflow and the newly downloaded Python wheel/sdist passed byte/metadata/archive/source checks, strict Twine, offline installation, actual import and CLI checks.
- The 10 unchanged runtime archives reuse complete cache bytes freshly hashed against new asset metadata and the existing runtime source release. They were not rebuilt or re-executed. SHA256SUMS covers all 12 payloads. This is not a new runtime-hardware claim.
- No full repository-suite, production-environment upgrade, Nano benchmark or adoption/growth claim is made.
What's Changed
- fix(runtime): decode every batch in ContextualParaformer and SeacoParaformer by @tanishqbaweja in #3838
- fix(runtime): release ONNX hotword batching fix as 0.4.7 by @LauraGPT in #3839
- fix(runtime): release Torch hotword batching fix as 0.1.5 by @LauraGPT in #3840
- fix(auto): honor merge_length_s passed to generate() by @MohammadHijjawi97 in #3841
- fix(vad): apply the offline dynamic silence schedule per frame by @lingfengyao in #3833
- fix(runtime): handle blank and incomplete CMVN files by @BillVan1945 in #3842
- fix(runtime): release ONNX CMVN parser fix as 0.4.8 by @LauraGPT in #3843
- fix(runtime): release Torch CMVN parser fix as 0.1.6 by @LauraGPT in #3844
- Release FunASR 1.4.22 by @LauraGPT in #3845
New Contributors
- @lingfengyao made their first contribution in #3833
- @BillVan1945 made their first contribution in #3842
Full Changelog: v1.4.21...v1.4.22
Runtime downloads
This Python release pairs with the current prebuilt llama.cpp / GGUF runtime release: runtime-llamacpp-v0.2.6.
The same verified runtime assets are attached directly to this Python release so users can find the package and self-contained llama-funasr-* binaries in one place.
| Platform | Asset | SHA-256 |
|---|---|---|
| Linux arm64 | funasr-llamacpp-linux-arm64.tar.gz | 7bca29cfa3c9a08e235a62212ca9e00f6656e59a8f07078966a2bfda1e5aa1f9 |
| Linux x64 AVX2 | funasr-llamacpp-linux-x64-avx2.tar.gz | aaebc5470f846ce915200b35d6e9f9bd0a0d3ed399d39e49bdeb7a1f1782bc70 |
| Linux x64 Vulkan | funasr-llamacpp-linux-x64-vulkan.tar.gz | f02d41e98e9d4041f0896661007193810f025484d2175958f7c1313d5c90ec46 |
| Linux x64 portable | funasr-llamacpp-linux-x64.tar.gz | 779967de1c528c2be966bcc47f246e7d3e6fcdb748d9491263062f4120f35e52 |
| macOS arm64 | funasr-llamacpp-macos-arm64.tar.gz | bda59474202b887190f59d25b7b42c714469efae71276072c12fa0a38de68792 |
| Windows x64 AVX2 | funasr-llamacpp-windows-x64-avx2.zip | 062cda8fefadd31c3e811227116daccf448a8520f4b0bb168d225c896e65ebbd |
| Windows x64 CUDA Blackwell (sm_120) | funasr-llamacpp-windows-x64-cuda-blackwell.zip | e32961a753f40888182f352fa551159c5165a6a77718ae4ade316aedfea4b1c2 |
| Windows x64 CUDA | funasr-llamacpp-windows-x64-cuda.zip | 148657911fb666b7af6ec43af2e23a0984e3259012b4c39f95631b717feb6840 |
| Windows x64 Vulkan | funasr-llamacpp-windows-x64-vulkan.zip | debf8007e55011cad06081e7b8a78972f1b8fe672bc324d41e650d68821f6a6a |
| Windows x64 portable | funasr-llamacpp-windows-x64.zip | f6a73a548413ba9fbaf2145263ea66ec53cbdad1fb11790dbeeee493e339492e |
Quick start: download one asset, unpack it, then run the bundled download-funasr-model.sh <sensevoice|paraformer|nano> helper and one of llama-funasr-cli, llama-funasr-sensevoice, or llama-funasr-paraformer.
For Python users, install from PyPI:
python -m pip install -U "funasr==1.4.22"
