From 6e69d784e4814c3dbe35e8f70c6cf4b920c8b20b Mon Sep 17 00:00:00 2001 From: 天地 <tiandiweizun@gmail.com> Date: 星期三, 19 三月 2025 23:10:13 +0800 Subject: [PATCH] 1. bug fix:list(mean)和list(var)，由于mean和var是numpy，导致写入到文件的格式错误，参考上面的话，大概率是list(mean.tolist())，其实外层list没有必要 (#2437) --- 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