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篇名
Multiple Scene Sentiment Analysis Based on Chinese Speech and Text
並列篇名
Multiple Scene Sentiment Analysis Based on Chinese Speech and Text
作者 Haiyuan Guo (Haiyuan Guo)Xuegang Zhan (Xuegang Zhan)Chengying Chi (Chengying Chi)
英文摘要

This paper proposes a multi-scene sentiment analysis model for Chinese speech and text based on CNN-BiGRU-CTC + ERNIE-BiLSTM. The model is applied to the intelligent customer service scenario. While conducting voice interaction, intelligent customer service can obtain the user’s current emotion, to give a more humane answer and improve the user experience. All the training data sets in this paper adopted public data sets such as Aishell-1 and NLPCC 2014, etc.We have been able to achieve a testing accuracy of about 94.5%. The accuracy is improved by 5.24% compared to the latest speech sentiment analysis model that uses audio as a feature. The advantage of this paper is that it adopts the ERNIE language pre-training model to conduct sentiment analysis on speech signals, which still has a good classification accuracy in the case of individual wrong words in speech recognition.

 

起訖頁 165-178
關鍵詞 ERNIEbi-directional long-short term memoryconvolutional neural networksCTCmulti-scenebidirectional gated recurrent unitintelligent customer service
刊名 電腦學刊  
期數 202202 (33:1期)
該期刊-上一篇 An Analysis Model of Potential Topics in English Essays Based on Semantic Space
該期刊-下一篇 Research for Fault Diagnosis Method and System for Diesel Engine Based on ANFIS
 

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