From e09d17de6088e3205ad9e3c85ec01b4fa0531587 Mon Sep 17 00:00:00 2001
From: yhliang <429259365@qq.com>
Date: 星期四, 13 四月 2023 15:09:04 +0800
Subject: [PATCH] add m2met2 docs cn version

---
 docs_m2met2/Baseline.md |    2 +-
 1 files changed, 1 insertions(+), 1 deletions(-)

diff --git a/docs_m2met2/Baseline.md b/docs_m2met2/Baseline.md
index 0bd09b3..975fab8 100644
--- a/docs_m2met2/Baseline.md
+++ b/docs_m2met2/Baseline.md
@@ -1,6 +1,6 @@
 # Baseline
 ## Overview
-We provide an end-to-end sa-asr baseline conducted on [FunASR](https://github.com/alibaba-damo-academy/FunASR) as a receipe. The model architecture is shown in Figure 3. The SpeakerEncoder is initialized with a pre-trained [speaker verification model](https://modelscope.cn/models/damo/speech_xvector_sv-zh-cn-cnceleb-16k-spk3465-pytorch/summary) from [ModelScope](https://modelscope.cn/home). This speaker verification model is also be used to extract the speaker embedding in the speaker profile. 
+We provide an end-to-end sa-asr baseline conducted on [FunASR](https://github.com/alibaba-damo-academy/FunASR) as a receipe. The model architecture is shown in Figure 2. The SpeakerEncoder is initialized with a pre-trained [speaker verification model](https://modelscope.cn/models/damo/speech_xvector_sv-zh-cn-cnceleb-16k-spk3465-pytorch/summary) from [ModelScope](https://modelscope.cn/home). This speaker verification model is also be used to extract the speaker embedding in the speaker profile. 
 
 ![model archietecture](images/sa_asr_arch.png)
 

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