From b0f4910de6dc91c13828026fb5bdd4f15d8636f3 Mon Sep 17 00:00:00 2001
From: shixian.shi <shixian.shi@alibaba-inc.com>
Date: 星期二, 27 六月 2023 20:11:30 +0800
Subject: [PATCH] update

---
 egs_modelscope/asr/paraformer/speech_paraformer-large-contextual_asr_nat-zh-cn-16k-common-vocab8404/demo.py |    4 ++++
 1 files changed, 4 insertions(+), 0 deletions(-)

diff --git a/egs_modelscope/asr/paraformer/speech_paraformer-large-contextual_asr_nat-zh-cn-16k-common-vocab8404/demo.py b/egs_modelscope/asr/paraformer/speech_paraformer-large-contextual_asr_nat-zh-cn-16k-common-vocab8404/demo.py
index bec6f05..e5e9097 100644
--- a/egs_modelscope/asr/paraformer/speech_paraformer-large-contextual_asr_nat-zh-cn-16k-common-vocab8404/demo.py
+++ b/egs_modelscope/asr/paraformer/speech_paraformer-large-contextual_asr_nat-zh-cn-16k-common-vocab8404/demo.py
@@ -3,6 +3,10 @@
 
 param_dict = dict()
 param_dict['hotword'] = "https://isv-data.oss-cn-hangzhou.aliyuncs.com/ics/MaaS/ASR/test_audio/hotword.txt"
+param_dict['clas_scale'] = 1.00  # 1.50 # set it larger if you want high recall (sacrifice general accuracy)
+# 13% relative recall raise over internal hotword test set (45%->51%)
+# CER might raise when utterance contains no hotword
+
 inference_pipeline = pipeline(
     task=Tasks.auto_speech_recognition,
     model="damo/speech_paraformer-large-contextual_asr_nat-zh-cn-16k-common-vocab8404",

--
Gitblit v1.9.1