v1.4.23

Final Publication Acceptance

GitHub Release and PyPI 1.4.23 are both published. Both distributions were downloaded from official PyPI and match the accepted GitHub assets by SHA-256 and size:

• funasr-1.4.23-py3-none-any.whl: 1014744 bytes; SHA-256 28f6696ad882d1273c371675ac35b427d2e548a2e736e42ef16d56cd96d17785.
• funasr-1.4.23.tar.gz: 1075334 bytes; SHA-256 89a2e1ba43468391bd603e952dd6fe306020719d82f99cd15bbdd2b130afd2f3.

FunASR 1.4.23

Source: efe5504e388613e5298e1f93d5ca9f861700b489 / tag v1.4.23.

Fix

Deliver #3849: initialize the valid-frame cursor for the online frontend with lfr_m=lfr_n=1, and avoid redundant empty final offline VAD chunks for exact input multiples. Deliver #3783: supplied token_list IDs map to model pieces before text conversion. With a supplied vocabulary, SentencePiece ids2tokens returns list[str] pieces; use tokens2text for text. Without a supplied vocabulary, legacy decoded-text behavior is preserved.

This does not claim pretrained ASR quality, Windows/NPU acceptance or a full repository-suite result.

The separately released funasr-onnx==0.4.9 and funasr-torch==0.1.6 have their own tags, packages and verification. This root-package release does not republish them. PR #3848 is not included. Explicit streaming-empty-input and nonempty tails producing zero features are outside the #3849 hardware acceptance; this release does not claim every EOS path is fixed.

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 and final wheels: 61 CPU contracts each covering no-LFR feature/chunk handling, analytic VAD finalization and tokenizer vocabulary semantics. Local tiny SentencePiece and controlled acoustic fixtures are not pretrained quality or hardware inference. All 439 package files and 13 entrypoints match the accepted source.
• Reused 16 direct FP32/BF16 frontend cases, 12 FP32 VAD cases and 12 FP32/BF16 tokenizer/decoder cases from #3849/#3783 after rehashing their sealed raw receipts and binding the exact source to the installed wheel. The earlier frontend run's six failed VAD cases remain recorded; the later corrected VAD run passed all 12. This release performs no new GPU execution and makes no pretrained-quality claim.
• The local candidate build and candidate/final package checks, tests and installations use private HOME/cache directories and separate network namespaces with verified network-unreachable probes. The final-tag build runs in GitHub Actions under the existing release workflow, not the local network namespace. No newly downloaded pretrained weights are used. The separately reported #3848 test-download incident is not an authorization or validation input for this release.
• Exact release-head and merged-main CI were accepted from their actual logs, with artifact inventories recorded. 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(frontend): handle default no-LFR online features by @LauraGPT in #3849
• fix(onnx): handle empty and short inputs in offline VAD by @BillVan1945 in #3846
• fix(tokenizer): respect the model vocabulary in ids2tokens by @carey-bk in #3783
• fix(onnx): handle empty punctuation input without consuming cache by @BillVan1945 in #3847
• fix(runtime): release ONNX VAD and punctuation fixes as 0.4.9 by @LauraGPT in #3850
• Release FunASR 1.4.23 by @LauraGPT in #3851

New Contributors

• @carey-bk made their first contribution in #3783

Full Changelog: v1.4.22...v1.4.23

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==1.4.23"