From 05c8eba11c51ca928eee9c041de1a4192e590aec Mon Sep 17 00:00:00 2001 From: nianjiuhuiyi <64776403+nianjiuhuiyi@users.noreply.github.com> Date: 星期五, 27 六月 2025 09:57:45 +0800 Subject: [PATCH] Fix: 修复c++后端服务因为空数组的异常退出，以及c++的http服务在收到Ctrl+C信号后无法正常退出 (#2571) --- docs/m2met2/Baseline.md | 8 ++++++-- 1 files changed, 6 insertions(+), 2 deletions(-) diff --git a/docs/m2met2/Baseline.md b/docs/m2met2/Baseline.md index 4e12162..12b6206 100644 --- a/docs/m2met2/Baseline.md +++ b/docs/m2met2/Baseline.md @@ -5,7 +5,7 @@  ## Quick start -To run the baseline, first you need to install FunASR and ModelScope. ([installation](https://alibaba-damo-academy.github.io/FunASR/en/installation.html)) +To run the baseline, first you need to install FunASR and ModelScope. ([installation](https://github.com/alibaba-damo-academy/FunASR#installation)) There are two startup scripts, `run.sh` for training and evaluating on the old eval and test sets, and `run_m2met_2023_infer.sh` for inference on the new test set of the Multi-Channel Multi-Party Meeting Transcription 2.0 ([M2MeT2.0](https://alibaba-damo-academy.github.io/FunASR/m2met2/index.html)) Challenge. Before running `run.sh`, you must manually download and unpack the [AliMeeting](http://www.openslr.org/119/) corpus and place it in the `./dataset` directory: ```shell @@ -31,4 +31,8 @@ ## Baseline results The results of the baseline system are shown in Table 3. The speaker profile adopts the oracle speaker embedding during training. However, due to the lack of oracle speaker label during evaluation, the speaker profile provided by an additional spectral clustering is used. Meanwhile, the results of using the oracle speaker profile on Eval and Test Set are also provided to show the impact of speaker profile accuracy. - \ No newline at end of file + +| |SI-CER(%) |cpCER(%) | +|:---------------|:------------:|----------:| +|oracle profile |32.72 |42.92 | +|cluster profile|32.73 |49.37 | \ No newline at end of file -- Gitblit v1.9.1