From 810046e3df4910c8f5c1a90e4b53aca45b3397e8 Mon Sep 17 00:00:00 2001
From: wuhongsheng <664116298@qq.com>
Date: 星期一, 01 七月 2024 10:42:58 +0800
Subject: [PATCH] 优化merge segments 参数，解决新闻联播男女主持人“晚上好”合并一个speakid问题 (#1861)
---
funasr/models/sond/encoder/ci_scorers.py | 18 ++++++------------
1 files changed, 6 insertions(+), 12 deletions(-)
diff --git a/funasr/models/sond/encoder/ci_scorers.py b/funasr/models/sond/encoder/ci_scorers.py
index 50056ee..a60560b 100644
--- a/funasr/models/sond/encoder/ci_scorers.py
+++ b/funasr/models/sond/encoder/ci_scorers.py
@@ -7,17 +7,14 @@
super().__init__()
def forward(
- self,
- xs_pad: torch.Tensor,
- spk_emb: torch.Tensor,
+ self,
+ xs_pad: torch.Tensor,
+ spk_emb: torch.Tensor,
):
# xs_pad: B, T, D
# spk_emb: B, N, D
scores = torch.matmul(xs_pad, spk_emb.transpose(1, 2))
return scores
-
- def convert_tf2torch(self, var_dict_tf, var_dict_torch):
- return {}
class CosScorer(torch.nn.Module):
@@ -25,14 +22,11 @@
super().__init__()
def forward(
- self,
- xs_pad: torch.Tensor,
- spk_emb: torch.Tensor,
+ self,
+ xs_pad: torch.Tensor,
+ spk_emb: torch.Tensor,
):
# xs_pad: B, T, D
# spk_emb: B, N, D
scores = F.cosine_similarity(xs_pad.unsqueeze(2), spk_emb.unsqueeze(1), dim=-1)
return scores
-
- def convert_tf2torch(self, var_dict_tf, var_dict_torch):
- return {}
--
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