update

egs_modelscope/asr/paraformer/speech_paraformer-large-contextual_asr_nat-zh-cn-16k-common-vocab8404/demo.py

@@ -3,6 +3,10 @@ from modelscope.utils.constant import Tasks
 
 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",