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篇名 |
Multiple Scene Sentiment Analysis Based on Chinese Speech and Text
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並列篇名 | Multiple Scene Sentiment Analysis Based on Chinese Speech and Text |
作者 | Haiyuan Guo、Xuegang Zhan、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.
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起訖頁 | 165-178 |
關鍵詞 | ERNIE、bi-directional long-short term memory、convolutional neural networks、CTC、multi-scene、bidirectional gated recurrent unit、intelligent customer service |
刊名 | 電腦學刊 |
期數 | 202202 (33:1期) |
DOI |
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