基於CNN+LSTM Model之語音情緒識別

Speech Emotion Recognition Based on CNN+LSTM Model

由於智能對話助理服務的普及，語音情緒辨識已經變得越來越重要。在人與機器的溝通中，情緒辨識與情感分析能夠增強機器與人類的互動。本研究使用CNN+LSTM模型實作語音情緒辨識(Speech Emotion Recognition, SER)處理並進行預測。從實驗結果得知使用CNN+LSTM模型相對於使用傳統NN模型取得更好的效能。

Due to the popularity of intelligent dialogue assistant services, speech emotion recognition has become more and more important. In the communication between humans and machines, emotion recognition and emotion analysis can enhance the interaction between machines and humans. This study uses the CNN+LSTM model to implement speech emotion recognition (SER) processing and prediction. From the experimental results, it is known that using the CNN+LSTM model achieves better performance than using the traditional NN model.