chore(release): prepare 1.4.4

README.md

@@ -330,6 +330,7 @@ asset is published.
 
 ## What's new
 
+- 2026/08/26: **v1.4.4 on PyPI** — realtime WebSocket decoding now batches compatible sessions instead of serializing every connection behind one process-wide lock. On the H100 regression workload, 12-client STOP p95 fell from 19.8 s to 0.4 s and 16-client aggregate throughput rose from 8.6x to 13.2x, with no client errors. This hotfix also restores compatibility with PyTorch releases that do not expose `torch.amp` and raises real runtime-binding exceptions. Upgrade with `python -m pip install -U "funasr==1.4.4"`. [Release ->](https://github.com/modelscope/FunASR/releases/tag/v1.4.4)
 - 2026/08/21: **v1.4.3 on PyPI** — `AutoModel(vad_model="silero-vad")` now offers an optional Silero VAD adapter with millisecond segments, configurable thresholds, 8/16 kHz input, ONNX mode, and bounded segment lengths. Upgrade with `python -m pip install -U "funasr==1.4.3"`; enable the adapter with `python -m pip install -U "funasr[silero]==1.4.3"`. Speaker diarization with a known speaker count now routes large embedding sets through fixed-K clustering instead of memory-heavy dense spectral clustering. [Release ->](https://github.com/modelscope/FunASR/releases/tag/v1.4.3)
 - 2026/08/14: **v1.4.2 on PyPI** — punctuation-aware sentence alignment now preserves subtitle segmentation when a punctuation token boundary splits a timestamped ASR word. Distributed training now synchronizes DDP/FSDP gradients on the final microbatch of each accumulation window and initializes DeepSpeed/FSDP mode from the resolved configuration. The tagged source also includes llama.cpp SRT output and the v0.2.0 AMD Vulkan submission updates. Install with `python -m pip install -U "funasr==1.4.2"`. [Release ->](https://github.com/modelscope/FunASR/releases/tag/v1.4.2)
 - 2026/08/11: **llama.cpp runtime v0.2.0** — pins upstream llama.cpp at `803b7fca` and publishes nine SHA-256-listed Linux, macOS, and Windows archives from one tested workflow. Fun-ASR-Nano, SenseVoice, and Paraformer CLIs can now write SRT subtitles; Vulkan startup reports actionable AMD diagnostics and a CPU fallback. The AMD Windows Vulkan crash fix still awaits confirmation on the reporter's hardware. [Download matrix & quickstart ->](https://www.funasr.com/en/deploy/llama-cpp.html) · [Release ->](https://github.com/modelscope/FunASR/releases/tag/runtime-llamacpp-v0.2.0)

README_ja.md

@@ -99,6 +99,7 @@ Whisper は単一モデルですが、**FunASR はツールキット**です—
 
 ## 最新情報
 
+- 2026/08/26：**v1.4.4 を PyPI に公開** — realtime WebSocket decode は、全 connection を 1 つの process-wide lock で直列化せず、互換性のある session を batch 処理するようになりました。H100 regression workload では、12 client の STOP p95 が 19.8 秒から 0.4 秒に短縮され、16 client の aggregate throughput は 8.6x から 13.2x に向上し、client error は 0 件でした。この hotfix は `torch.amp` を持たない PyTorch release との互換性も復元し、runtime binding から実際の例外を送出します。更新：`python -m pip install -U "funasr==1.4.4"`。[Release →](https://github.com/modelscope/FunASR/releases/tag/v1.4.4)
 - 2026/08/21：**v1.4.3 を PyPI に公開** — `AutoModel(vad_model="silero-vad")` で任意の Silero VAD アダプターを利用でき、ミリ秒単位の区間、しきい値、8/16 kHz 入力、ONNX mode、最大区間長を設定できます。更新：`python -m pip install -U "funasr==1.4.3"`。アダプターの有効化：`python -m pip install -U "funasr[silero]==1.4.3"`。話者数が既知の話者ダイアライゼーションは、大規模 embedding をメモリ負荷の高い密なスペクトラルクラスタリングではなく fixed-K クラスタリングで処理します。[Release →](https://github.com/modelscope/FunASR/releases/tag/v1.4.3)
 - 2026/08/14：**v1.4.2 を PyPI に公開** — 句読点モデルの token 境界がタイムスタンプ付き ASR 単語の内部にある場合でも、文アラインメントが字幕分割を正しく保持するようになりました。分散学習では、各勾配累積 window の最後の microbatch で DDP/FSDP 勾配を同期し、解決済み設定から DeepSpeed/FSDP mode を初期化します。対応する GitHub ソース tag には llama.cpp SRT 出力と v0.2.0 の AMD Vulkan submission 更新も含まれます。インストール：`python -m pip install -U "funasr==1.4.2"`。[Release →](https://github.com/modelscope/FunASR/releases/tag/v1.4.2)
 - 2026/08/11：**llama.cpp runtime v0.2.0** — upstream llama.cpp を `803b7fca` に固定し、同一のテスト済み workflow から SHA-256 付きの Linux、macOS、Windows 向け 9 archive を公開しました。Fun-ASR-Nano、SenseVoice、Paraformer CLI は SRT 字幕を出力でき、Vulkan 起動時には AMD 向け診断と CPU fallback を案内します。AMD Windows Vulkan crash の修正は、報告者の実機確認待ちです。[ダウンロード一覧と quickstart →](https://www.funasr.com/en/deploy/llama-cpp.html) · [Release →](https://github.com/modelscope/FunASR/releases/tag/runtime-llamacpp-v0.2.0)

README_ko.md

@@ -99,6 +99,7 @@ Whisper는 단일 모델이지만, **FunASR는 툴킷**입니다. 용도에 맞
 
 ## 최신 소식
 
+- 2026/08/26: **v1.4.4 PyPI 공개** — realtime WebSocket decode가 모든 connection을 하나의 process-wide lock으로 직렬화하지 않고 호환되는 session을 batch 처리합니다. H100 regression workload에서 12-client STOP p95는 19.8초에서 0.4초로 줄었고, 16-client aggregate throughput은 8.6x에서 13.2x로 향상됐으며 client error는 0건이었습니다. 이 hotfix는 `torch.amp`가 없는 PyTorch release와의 호환성도 복원하고 runtime binding에서 실제 예외를 발생시킵니다. 업데이트: `python -m pip install -U "funasr==1.4.4"`. [Release →](https://github.com/modelscope/FunASR/releases/tag/v1.4.4)
 - 2026/08/21: **v1.4.3 PyPI 공개** — `AutoModel(vad_model="silero-vad")`에서 선택형 Silero VAD adapter를 사용할 수 있으며, 밀리초 단위 구간, threshold, 8/16 kHz 입력, ONNX mode, 최대 구간 길이를 지원합니다. 업데이트: `python -m pip install -U "funasr==1.4.3"`. Adapter 활성화: `python -m pip install -U "funasr[silero]==1.4.3"`. 화자 수를 알고 있는 speaker diarization은 대규모 embedding을 메모리 사용량이 큰 dense spectral clustering 대신 fixed-K clustering으로 처리합니다. [Release →](https://github.com/modelscope/FunASR/releases/tag/v1.4.3)
 - 2026/08/14: **v1.4.2 PyPI 공개** — 문장부호 모델의 token 경계가 타임스탬프가 있는 ASR 단어 내부에 놓여도 문장 정렬이 올바른 자막 분할을 유지합니다. 분산 학습은 각 gradient accumulation window의 마지막 microbatch에서 DDP/FSDP gradient를 동기화하고, 해석된 설정에서 DeepSpeed/FSDP mode를 초기화합니다. 해당 GitHub 소스 tag에는 llama.cpp SRT 출력과 v0.2.0 AMD Vulkan submission 업데이트도 포함됩니다. 설치: `python -m pip install -U "funasr==1.4.2"`. [Release →](https://github.com/modelscope/FunASR/releases/tag/v1.4.2)
 - 2026/08/11: **llama.cpp runtime v0.2.0** — upstream llama.cpp를 `803b7fca`로 고정하고, 하나의 검증된 workflow에서 SHA-256 값이 제공되는 Linux, macOS, Windows용 archive 9개를 공개했습니다. Fun-ASR-Nano, SenseVoice 및 Paraformer CLI는 SRT 자막을 출력할 수 있으며, Vulkan 시작 시 AMD 진단 정보와 CPU fallback을 안내합니다. AMD Windows Vulkan crash 수정은 제보자의 실제 하드웨어 확인을 기다리고 있습니다. [다운로드 목록 및 quickstart →](https://www.funasr.com/en/deploy/llama-cpp.html) · [Release →](https://github.com/modelscope/FunASR/releases/tag/runtime-llamacpp-v0.2.0)

README_zh.md

@@ -149,6 +149,7 @@ Whisper 是单个模型，**FunASR 是一个工具箱**——按场景挑模型
 
 ## 最新动态
 
+- 2026/08/26：**v1.4.4 已发布到 PyPI** — 实时 WebSocket 解码会对兼容会话进行批处理，不再让所有连接排队经过同一个进程级锁。在 H100 回归负载下，12 路 STOP p95 从 19.8 秒降至 0.4 秒，16 路聚合吞吐从 8.6x 提升到 13.2x，且客户端零错误。本热修复同时兼容不提供 `torch.amp` 的 PyTorch 版本，并让运行时绑定抛出真实异常。升级命令：`python -m pip install -U "funasr==1.4.4"`。[发布页 →](https://github.com/modelscope/FunASR/releases/tag/v1.4.4)
 - 2026/08/21：**v1.4.3 已发布到 PyPI** — `AutoModel(vad_model="silero-vad")` 现可选用 Silero VAD 适配器，返回毫秒级片段，并支持阈值、8/16 kHz 输入、ONNX 模式和最长片段限制。基础升级命令：`python -m pip install -U "funasr==1.4.3"`；启用该适配器：`python -m pip install -U "funasr[silero]==1.4.3"`。已知说话人数的说话人分离在大规模 embedding 输入下改用固定 K 聚类，避免内存开销较高的稠密谱聚类。[发布页 →](https://github.com/modelscope/FunASR/releases/tag/v1.4.3)
 - 2026/08/14：**v1.4.2 已发布到 PyPI** — 标点模型的 token 边界落在带时间戳的 ASR 词内部时，句子对齐现在仍能保留正确的字幕分段。分布式训练会在每个梯度累积窗口的最后一个 microbatch 同步 DDP/FSDP 梯度，并从解析后的配置正确初始化 DeepSpeed/FSDP 模式。对应 GitHub 源码 tag 同时包含 llama.cpp SRT 输出和 v0.2.0 AMD Vulkan submission 更新。安装命令：`python -m pip install -U "funasr==1.4.2"`。[发布页 →](https://github.com/modelscope/FunASR/releases/tag/v1.4.2)
 - 2026/08/11：**llama.cpp runtime v0.2.0** — 统一固定上游 llama.cpp 到 `803b7fca`，通过同一套测试工作流发布 9 个带 SHA-256 校验值的 Linux、macOS 与 Windows 压缩包。Fun-ASR-Nano、SenseVoice 和 Paraformer CLI 现在可直接输出 SRT 字幕；Vulkan 启动会给出可操作的 AMD 诊断信息和 CPU fallback。AMD Windows Vulkan 崩溃修复仍等待 issue 报告者在原硬件上确认。[下载矩阵与快速开始 →](https://www.funasr.com/deploy/llama-cpp.html) · [发布页 →](https://github.com/modelscope/FunASR/releases/tag/runtime-llamacpp-v0.2.0)

funasr/version.txt

@@ -1 +1 @@
-1.4.3
+1.4.4

tests/test_release_version_contract.py

@@ -2,7 +2,7 @@
 
 
 ROOT = Path(__file__).resolve().parents[1]
-RELEASE_VERSION = "1.4.3"
+RELEASE_VERSION = "1.4.4"
 README_FILES = ("README.md", "README_zh.md", "README_ja.md", "README_ko.md")